Selective laser melting of Ni-rich NiTi: selection of process parameters and the superelastic response

NASA Astrophysics Data System (ADS)

Shayesteh Moghaddam, Narges; Saedi, Soheil; Amerinatanzi, Amirhesam; Saghaian, Ehsan; Jahadakbar, Ahmadreza; Karaca, Haluk; Elahinia, Mohammad

2018-03-01

Material and mechanical properties of NiTi shape memory alloys strongly depend on the fabrication process parameters and the resulting microstructure. In selective laser melting, the combination of parameters such as laser power, scanning speed, and hatch spacing determine the microstructural defects, grain size and texture. Therefore, processing parameters can be adjusted to tailor the microstructure and mechanical response of the alloy. In this work, NiTi samples were fabricated using Ni50.8Ti (at.%) powder via SLM PXM by Phenix/3D Systems and the effects of processing parameters were systematically studied. The relationship between the processing parameters and superelastic properties were investigated thoroughly. It will be shown that energy density is not the only parameter that governs the material response. It will be shown that hatch spacing is the dominant factor to tailor the superelastic response. It will be revealed that with the selection of right process parameters, perfect superelasticity with recoverable strains of up to 5.6% can be observed in the as-fabricated condition.

Evolution of process control parameters during extended co-composting of green waste and solid fraction of cattle slurry to obtain growing media.

PubMed

Cáceres, Rafaela; Coromina, Narcís; Malińska, Krystyna; Marfà, Oriol

2015-03-01

This study aimed to monitor process parameters when two by-products (green waste - GW, and the solid fraction of cattle slurry - SFCS) were composted to obtain growing media. Using compost in growing medium mixtures involves prolonged composting processes that can last at least half a year. It is therefore crucial to study the parameters that affect compost stability as measured in the field in order to shorten the composting process at composting facilities. Two mixtures were prepared: GW25 (25% GW and 75% SFCS, v/v) and GW75 (75% GW and 25% SFCS, v/v). The different raw mixtures resulted in the production of two different growing media, and the evolution of process management parameters was different. A new parameter has been proposed to deal with attaining the thermophilic temperature range and maintaining it during composting, not only it would be useful to optimize composting processes, but also to assess the hygienization degree. Copyright © 2014 Elsevier Ltd. All rights reserved.

Investigation on influence of Wurster coating process parameters for the development of delayed release minitablets of Naproxen.

PubMed

Shah, Neha; Mehta, Tejal; Aware, Rahul; Shetty, Vasant

2017-12-01

The present work aims at studying process parameters affecting coating of minitablets (3 mm in diameter) through Wurster coating process. Minitablets of Naproxen with high drug loading were manufactured using 3 mm multi-tip punches. The release profile of core pellets (published) and minitablets was compared with that of marketed formulation. The core formulation of minitablets was found to show similarity in dissolution profile with marketed formulation and hence was further carried forward for functional coating over it. Wurster processing was implemented to pursue functional coating over core formulation. Different process parameters were screened and control strategy was applied for factors significantly affecting the process. Modified Plackett Burman Design was applied for studying important factors. Based on the significant factors and minimum level of coating required for functionalization, optimized process was executed. Final coated batch was evaluated for coating thickness, surface morphology, and drug release study.

Effect of Burnishing Parameters on Surface Finish

NASA Astrophysics Data System (ADS)

Shirsat, Uddhav; Ahuja, Basant; Dhuttargaon, Mukund

2017-08-01

Burnishing is cold working process in which hard balls are pressed against the surface, resulting in improved surface finish. The surface gets compressed and then plasticized. This is a highly finishing process which is becoming more popular. Surface quality of the product improves its aesthetic appearance. The product made up of aluminum material is subjected to burnishing process during which kerosene is used as a lubricant. In this study factors affecting burnishing process such as burnishing force, speed, feed, work piece diameter and ball diameter are considered as input parameters while surface finish is considered as an output parameter In this study, experiments are designed using 25 factorial design in order to analyze the relationship between input and output parameters. The ANOVA technique and F-test are used for further analysis.

Application of Quality by Design to the characterization of the cell culture process of an Fc-Fusion protein.

PubMed

Rouiller, Yolande; Solacroup, Thomas; Deparis, Véronique; Barbafieri, Marco; Gleixner, Ralf; Broly, Hervé; Eon-Duval, Alex

2012-06-01

The production bioreactor step of an Fc-Fusion protein manufacturing cell culture process was characterized following Quality by Design principles. Using scientific knowledge derived from the literature and process knowledge gathered during development studies and manufacturing to support clinical trials, potential critical and key process parameters with a possible impact on product quality and process performance, respectively, were determined during a risk assessment exercise. The identified process parameters were evaluated using a design of experiment approach. The regression models generated from the data allowed characterizing the impact of the identified process parameters on quality attributes. The main parameters having an impact on product titer were pH and dissolved oxygen, while those having the highest impact on process- and product-related impurities and variants were pH and culture duration. The models derived from characterization studies were used to define the cell culture process design space. The design space limits were set in such a way as to ensure that the drug substance material would consistently have the desired quality. Copyright © 2012 Elsevier B.V. All rights reserved.

Study on loading path optimization of internal high pressure forming process

NASA Astrophysics Data System (ADS)

Jiang, Shufeng; Zhu, Hengda; Gao, Fusheng

2017-09-01

In the process of internal high pressure forming, there is no formula to describe the process parameters and forming results. The article use numerical simulation to obtain several input parameters and corresponding output result, use the BP neural network to found their mapping relationship, and with weighted summing method make each evaluating parameters to set up a formula which can evaluate quality. Then put the training BP neural network into the particle swarm optimization, and take the evaluating formula of the quality as adapting formula of particle swarm optimization, finally do the optimization and research at the range of each parameters. The results show that the parameters obtained by the BP neural network algorithm and the particle swarm optimization algorithm can meet the practical requirements. The method can solve the optimization of the process parameters in the internal high pressure forming process.

Assessment of Process Capability: the case of Soft Drinks Processing Unit

NASA Astrophysics Data System (ADS)

Sri Yogi, Kottala

2018-03-01

The process capability studies have significant impact in investigating process variation which is important in achieving product quality characteristics. Its indices are to measure the inherent variability of a process and thus to improve the process performance radically. The main objective of this paper is to understand capability of the process being produced within specification of the soft drinks processing unit, a premier brands being marketed in India. A few selected critical parameters in soft drinks processing: concentration of gas volume, concentration of brix, torque of crock has been considered for this study. Assessed some relevant statistical parameters: short term capability, long term capability as a process capability indices perspective. For assessment we have used real time data of soft drinks bottling company which is located in state of Chhattisgarh, India. As our research output suggested reasons for variations in the process which is validated using ANOVA and also predicted Taguchi cost function, assessed also predicted waste monetarily this shall be used by organization for improving process parameters. This research work has substantially benefitted the organization in understanding the various variations of selected critical parameters for achieving zero rejection.

PMMA/PS coaxial electrospinning: a statistical analysis on processing parameters

NASA Astrophysics Data System (ADS)

Rahmani, Shahrzad; Arefazar, Ahmad; Latifi, Masoud

2017-08-01

Coaxial electrospinning, as a versatile method for producing core-shell fibers, is known to be very sensitive to two classes of influential factors including material and processing parameters. Although coaxial electrospinning has been the focus of many studies, the effects of processing parameters on the outcomes of this method have not yet been well investigated. A good knowledge of the impacts of processing parameters and their interactions on coaxial electrospinning can make it possible to better control and optimize this process. Hence, in this study, the statistical technique of response surface method (RSM) using the design of experiments on four processing factors of voltage, distance, core and shell flow rates was applied. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), oil immersion and Fluorescent microscopy were used to characterize fiber morphology. The core and shell diameters of fibers were measured and the effects of all factors and their interactions were discussed. Two polynomial models with acceptable R-squares were proposed to describe the core and shell diameters as functions of the processing parameters. Voltage and distance were recognized as the most significant and influential factors on shell diameter, while core diameter was mainly under the influence of core and shell flow rates besides the voltage.

Experimental investigations on the effect of process parameters with the use of minimum quantity solid lubrication in turning

NASA Astrophysics Data System (ADS)

Makhesana, Mayur A.; Patel, K. M.; Mawandiya, B. K.

2018-04-01

Turning process is a very basic process in any field of mechanical application. During turning process, most of the energy is converted into heat because of the friction between work piece and tool. Heat generation can affect the surface quality of the work piece and tool life. To reduce the heat generation, Conventional Lubrication process is used in most of the industry. Minimum quantity lubrication has been an effective alternative to improve the performance of machining process. In this present work, effort has been made to study the effect of various process parameters on the surface roughness and power consumption during turning of EN8 steel material. Result revealed the effect of depth of cut and feed on the obtained surface roughness value. Further the effect of solid lubricant has been also studied and optimization of process parameters is also done for the turning process.

Code IN Exhibits - Supercomputing 2000

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; Biswas, Rupak; VanderWijngaart, Rob F.; Kwak, Dochan (Technical Monitor)

2000-01-01

The creation of parameter study suites has recently become a more challenging problem as the parameter studies have become multi-tiered and the computational environment has become a supercomputer grid. The parameter spaces are vast, the individual problem sizes are getting larger, and researchers are seeking to combine several successive stages of parameterization and computation. Simultaneously, grid-based computing offers immense resource opportunities but at the expense of great difficulty of use. We present ILab, an advanced graphical user interface approach to this problem. Our novel strategy stresses intuitive visual design tools for parameter study creation and complex process specification, and also offers programming-free access to grid-based supercomputer resources and process automation.

Effect of Friction Stir Process Parameters on the Mechanical and Thermal Behavior of 5754-H111 Aluminum Plates.

PubMed

Serio, Livia Maria; Palumbo, Davide; De Filippis, Luigi Alberto Ciro; Galietti, Umberto; Ludovico, Antonio Domenico

2016-02-23

A study of the Friction Stir Welding (FSW) process was carried out in order to evaluate the influence of process parameters on the mechanical properties of aluminum plates (AA5754-H111). The process was monitored during each test by means of infrared cameras in order to correlate temperature information with eventual changes of the mechanical properties of joints. In particular, two process parameters were considered for tests: the welding tool rotation speed and the welding tool traverse speed. The quality of joints was evaluated by means of destructive and non-destructive tests. In this regard, the presence of defects and the ultimate tensile strength (UTS) were investigated for each combination of the process parameters. A statistical analysis was carried out to assess the correlation between the thermal behavior of joints and the process parameters, also proving the capability of Infrared Thermography for on-line monitoring of the quality of joints.

Effect of Friction Stir Process Parameters on the Mechanical and Thermal Behavior of 5754-H111 Aluminum Plates

PubMed Central

Serio, Livia Maria; Palumbo, Davide; De Filippis, Luigi Alberto Ciro; Galietti, Umberto; Ludovico, Antonio Domenico

2016-01-01

A study of the Friction Stir Welding (FSW) process was carried out in order to evaluate the influence of process parameters on the mechanical properties of aluminum plates (AA5754-H111). The process was monitored during each test by means of infrared cameras in order to correlate temperature information with eventual changes of the mechanical properties of joints. In particular, two process parameters were considered for tests: the welding tool rotation speed and the welding tool traverse speed. The quality of joints was evaluated by means of destructive and non-destructive tests. In this regard, the presence of defects and the ultimate tensile strength (UTS) were investigated for each combination of the process parameters. A statistical analysis was carried out to assess the correlation between the thermal behavior of joints and the process parameters, also proving the capability of Infrared Thermography for on-line monitoring of the quality of joints. PMID:28773246

Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

NASA Astrophysics Data System (ADS)

Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

2017-10-01

Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

Influence of Different Container Closure Systems and Capping Process Parameters on Product Quality and Container Closure Integrity (CCI) in GMP Drug Product Manufacturing.

PubMed

Mathaes, Roman; Mahler, Hanns-Christian; Roggo, Yves; Huwyler, Joerg; Eder, Juergen; Fritsch, Kamila; Posset, Tobias; Mohl, Silke; Streubel, Alexander

2016-01-01

Capping equipment used in good manufacturing practice manufacturing features different designs and a variety of adjustable process parameters. The overall capping result is a complex interplay of the different capping process parameters and is insufficiently described in literature. It remains poorly studied how the different capping equipment designs and capping equipment process parameters (e.g., pre-compression force, capping plate height, turntable rotating speed) contribute to the final residual seal force of a sealed container closure system and its relation to container closure integrity and other drug product quality parameters. Stopper compression measured by computer tomography correlated to residual seal force measurements.In our studies, we used different container closure system configurations from different good manufacturing practice drug product fill & finish facilities to investigate the influence of differences in primary packaging, that is, vial size and rubber stopper design on the capping process and the capped drug product. In addition, we compared two large-scale good manufacturing practice manufacturing capping equipment and different capping equipment settings and their impact on product quality and integrity, as determined by residual seal force.The capping plate to plunger distance had a major influence on the obtained residual seal force values of a sealed vial, whereas the capping pre-compression force and the turntable rotation speed showed only a minor influence on the residual seal force of a sealed vial. Capping process parameters could not easily be transferred from capping equipment of different manufacturers. However, the residual seal force tester did provide a valuable tool to compare capping performance of different capping equipment. No vial showed any leakage greater than 10(-8)mbar L/s as measured by a helium mass spectrometry system, suggesting that container closure integrity was warranted in the residual seal force range tested for the tested container closure systems. Capping equipment used in good manufacturing practice manufacturing features different designs and a variety of adjustable process parameters. The overall capping result is a complex interplay of the different capping process parameters and is insufficiently described in the literature. It remains poorly studied how the different capping equipment designs and capping equipment process parameters contribute to the final capping result.In this study, we used different container closure system configurations from different good manufacturing process drug product fill & finish facilities to investigate the influence of the vial size and the rubber stopper design on the capping process. In addition, we compared two examples of large-scale good manufacturing process capping equipment and different capping equipment settings and their impact on product quality and integrity, as determined by residual seal force. © PDA, Inc. 2016.

An automatic alignment tool to improve repeatability of left ventricular function and dyssynchrony parameters in serial gated myocardial perfusion SPECT studies

PubMed Central

Zhou, Yanli; Faber, Tracy L.; Patel, Zenic; Folks, Russell D.; Cheung, Alice A.; Garcia, Ernest V.; Soman, Prem; Li, Dianfu; Cao, Kejiang; Chen, Ji

2013-01-01

Objective Left ventricular (LV) function and dyssynchrony parameters measured from serial gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) using blinded processing had a poorer repeatability than when manual side-by-side processing was used. The objective of this study was to validate whether an automatic alignment tool can reduce the variability of LV function and dyssynchrony parameters in serial gated SPECT MPI. Methods Thirty patients who had undergone serial gated SPECT MPI were prospectively enrolled in this study. Thirty minutes after the first acquisition, each patient was repositioned and a gated SPECT MPI image was reacquired. The two data sets were first processed blinded from each other by the same technologist in different weeks. These processed data were then realigned by the automatic tool, and manual side-by-side processing was carried out. All processing methods used standard iterative reconstruction and Butterworth filtering. The Emory Cardiac Toolbox was used to measure the LV function and dyssynchrony parameters. Results The automatic tool failed in one patient, who had a large, severe scar in the inferobasal wall. In the remaining 29 patients, the repeatability of the LV function and dyssynchrony parameters after automatic alignment was significantly improved from blinded processing and was comparable to manual side-by-side processing. Conclusion The automatic alignment tool can be an alternative method to manual side-by-side processing to improve the repeatability of LV function and dyssynchrony measurements by serial gated SPECT MPI. PMID:23211996

Early Shear Failure Prediction in Incremental Sheet Forming Process Using FEM and ANN

NASA Astrophysics Data System (ADS)

Moayedfar, Majid; Hanaei, Hengameh; Majdi Rani, Ahmad; Musa, Mohd Azam Bin; Sadegh Momeni, Mohammad

2018-03-01

The application of incremental sheet forming process as a rapid forming technique is rising in variety of industries such as aerospace, automotive and biomechanical purposes. However, the sheet failure is a big challenge in this process which leads wasting lots of materials. Hence, this study tried to propose a method to predict the early sheet failure in this process using mathematical solution. For the feasibility of the study, design of experiment with the respond surface method is employed to extract a set of experiments data for the simulation. The significant forming parameters were recognized and their integration was used for prediction system. Then, the results were inserted to the artificial neural network as input parameters to predict a vast range of applicable parameters avoiding sheet failure in ISF. The value of accuracy R2 ∼0.93 was obtained and the maximum sheet stretch in the depth of 25mm were recorded. The figures generate from the trend of interaction between effective parameters were provided for future studies.

Optimization of Gas Metal Arc Welding Process Parameters

NASA Astrophysics Data System (ADS)

Kumar, Amit; Khurana, M. K.; Yadav, Pradeep K.

2016-09-01

This study presents the application of Taguchi method combined with grey relational analysis to optimize the process parameters of gas metal arc welding (GMAW) of AISI 1020 carbon steels for multiple quality characteristics (bead width, bead height, weld penetration and heat affected zone). An orthogonal array of L9 has been implemented to fabrication of joints. The experiments have been conducted according to the combination of voltage (V), current (A) and welding speed (Ws). The results revealed that the welding speed is most significant process parameter. By analyzing the grey relational grades, optimal parameters are obtained and significant factors are known using ANOVA analysis. The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions.

Warpage analysis in injection moulding process

NASA Astrophysics Data System (ADS)

Hidayah, M. H. N.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

This study was concentrated on the effects of process parameters in plastic injection moulding process towards warpage problem by using Autodesk Moldflow Insight (AMI) software for the simulation. In this study, plastic dispenser of dental floss has been analysed with thermoplastic material of Polypropylene (PP) used as the moulded material and details properties of 80 Tonne Nessei NEX 1000 injection moulding machine also has been used in this study. The variable parameters of the process are packing pressure, packing time, melt temperature and cooling time. Minimization of warpage obtained from the optimization and analysis data from the Design Expert software. Integration of Response Surface Methodology (RSM), Center Composite Design (CCD) with polynomial models that has been obtained from Design of Experiment (DOE) is the method used in this study. The results show that packing pressure is the main factor that will contribute to the formation of warpage in x-axis and y-axis. While in z-axis, the main factor is melt temperature and packing time is the less significant among the four parameters in x, y and z-axes. From optimal processing parameter, the value of warpage in x, y and z-axis have been optimised by 21.60%, 26.45% and 24.53%, respectively.

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

PubMed

Markiewicz, Łukasz; Kubińska, Elżbieta

2015-01-01

This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of hot tasks inhibits correct information processing, probably because it is difficult to engage Type 2 processes in such circumstances. Individuals' Type 2 processing abilities (measured by the CRT) assist greater use of information in cold tasks but do not help in hot tasks.

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

PubMed Central

Markiewicz, Łukasz; Kubińska, Elżbieta

2015-01-01

Objective: This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Methods: Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Results: Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of hot tasks inhibits correct information processing, probably because it is difficult to engage Type 2 processes in such circumstances. Individuals' Type 2 processing abilities (measured by the CRT) assist greater use of information in cold tasks but do not help in hot tasks. PMID:26635652

Effects of process parameters on solid self-microemulsifying particles in a laboratory scale fluid bed.

PubMed

Mukherjee, Tusharmouli; Plakogiannis, Fotios M

2012-01-01

The purpose of this study was to select the critical process parameters of the fluid bed processes impacting the quality attribute of a solid self-microemulsifying (SME) system of albendazole (ABZ). A fractional factorial design (2(4-1)) with four parameters (spray rate, inlet air temperature, inlet air flow, and atomization air pressure) was created by MINITAB software. Batches were manufactured in a laboratory top-spray fluid bed at 625-g scale. Loss on drying (LOD) samples were taken throughout each batch to build the entire moisture profiles. All dried granulation were sieved using mesh 20 and analyzed for particle size distribution (PSD), morphology, density, and flow. It was found that as spray rate increased, sauter-mean diameter (D(s)) also increased. The effect of inlet air temperature on the peak moisture which is directly related to the mean particle size was found to be significant. There were two-way interactions between studied process parameters. The main effects of inlet air flow rate and atomization air pressure could not be found as the data were inconclusive. The partial least square (PLS) regression model was found significant (P < 0.01) and predictive for optimization. This study established a design space for the parameters for solid SME manufacturing process.

Nonlinear Multiscale Modeling of 3D Woven Fiber Composites under Ballistic Loading

DTIC Science & Technology

2013-07-11

contact parameters on the underlying damage processes is being studied and worked on. We further develop a material model suitable particularly for...of Material and Process Engineering. 2011/05/23 00:00:00, . : , TOTAL: 1 (d) Manuscripts Number of Peer-Reviewed Conference Proceeding publications...continuum damage mechanics suitable for polymer materials. The effect of contact parameters on the underlying damage processes is being studied and

Influence of process parameters on the effectiveness of photooxidative treatment of pharmaceuticals.

PubMed

Markic, Marinko; Cvetnic, Matija; Ukic, Sime; Kusic, Hrvoje; Bolanca, Tomislav; Bozic, Ana Loncaric

2018-03-21

In this study, UV-C/H 2 O 2 and UV-C/[Formula: see text] processes as photooxidative Advanced oxidation processes were applied for the treatment of seven pharmaceuticals, either already included in the Directive 2013/39/EU "watch list" (17α- ethynylestradiol, 17β-estradiol) or with potential to be added in the near future due to environmental properties and increasing consumption (azithromycin, carbamazepine, dexamethasone, erythromycin and oxytetracycline). The influence of process parameters (pH, oxidant concentration and type) on the pharmaceuticals degradation was studied through employed response surface modelling approach. It was established that degradation obeys first-order kinetic regime regardless structural differences and over entire range of studied process parameters. The results revealed that the effectiveness of UV-C/H 2 O 2 process is highly dependent on both initial pH and oxidant concentration. It was found that UV-C/[Formula: see text] process, exhibiting several times faster degradation of studied pharmaceuticals, is less sensitive to pH changes providing practical benefit to its utilization. The influence of water matrix on degradation kinetics of studied pharmaceuticals was studied through natural organic matter effects on single component and mixture systems.

Correlation of Selected Cognitive Abilities and Cognitive Processing Parameters: An Exploratory Study.

ERIC Educational Resources Information Center

Snow, Richard E.; And Others

This pilot study investigated some relationships between tested ability variables and processing parameters obtained from memory search and visual search tasks. The 25 undergraduates who participated had also participated in a previous investigation by Chiang and Atkinson. A battery of traditional ability tests and several film tests were…

Properties of pellets manufactured by wet extrusion/spheronization process using kappa-carrageenan: effect of process parameters.

PubMed

Thommes, Markus; Kleinebudde, Peter

2007-11-09

The aim of this study was to systematically evaluate the pelletization process parameters of kappa-carrageenan-containing formulations. The study dealt with the effect of 4 process parameters--screw speed, number of die holes, friction plate speed, and spheronizer temperature--on the pellet properties of shape, size, size distribution, tensile strength, and drug release. These parameters were varied systematically in a 2(4) full factorial design. In addition, 4 drugs--phenacetin, chloramphenicol, dimenhydrinate, and lidocaine hydrochloride--were investigated under constant process conditions. The most spherical pellets were achieved in a high yield by using a large number of die holes and a high spheronizer speed. There was no relevant influence of the investigated process parameters on the size distribution, mechanical stability, and drug release. The poorly soluble drugs, phenacetin and chloramphenicol, resulted in pellets with adequate shape, size, and tensile strength and a fast drug release. The salts of dimenhydrinate and lidocaine affected pellet shape, mechanical stability, and the drug release properties using an aqueous solution of pH 3 as a granulation liquid. In the case of dimenhydrinate, this was attributed to the ionic interactions with kappa-carrageenan, resulting in a stable matrix during dissolution that did not disintegrate. The effect of lidocaine is comparable to the effect of sodium ions, which suppress the gelling of carrageenan, resulting in pellets with fast disintegration and drug release characteristics. The pellet properties are affected by the process parameters and the active pharmaceutical ingredient used.

Drug recrystallization using supercritical anti-solvent (SAS) process with impinging jets: Effect of process parameters

NASA Astrophysics Data System (ADS)

Careno, Stéphanie; Boutin, Olivier; Badens, Elisabeth

2012-03-01

The aim of this study is to improve mixing in supercritical anti-solvent process (SAS) with impinging jets in order to form finer particles of sulfathiazole, a poorly water-soluble drug. The influence of several process parameters upon the powder characteristics is studied. Parameters are jets' velocity (0.25 m s-1 to 25.92 m s-1), molar ratio solvent/CO2 (2.5% to 20%), temperature (313 K to 343 K), pressure (10 MPa to 20 MPa) and sulfathiazole concentration in the organic solution (0.5% to 1.8%). Two solvents are used: acetone and methanol. Smaller particles with a more homogeneous morphology are obtained from acetone solutions. For the smallest jets' velocity, corresponding to a non-atomized jet, the stable polymorphic form is obtained, pure or in mixture. At this velocity, pressure is the most influential parameter controlling the polymorphic nature of the powder formed. The pure stable polymorph is formed at 20 MPa. Concerning the particle size, the most influential parameters are temperature and sulfathiazole concentration. The use of impinging jets with different process parameters allows the crystallization of four polymorphs among the five known, and particle sizes are varied. This work demonstrates the studied device ability of the polymorph and the size control. A comparison with the classical SAS process shows that particle size, size distribution and morphology of particles crystallized with impinging jets are different from the ones obtained with classical SAS introduction device in similar operating conditions. Mean particle sizes are significantly smaller and size distributions are narrower with impinging jets device.

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

NASA Technical Reports Server (NTRS)

Hartman, Brian Davis

1995-01-01

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

NASA Astrophysics Data System (ADS)

Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

2018-02-01

Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

Investigation into the influence of laser energy input on selective laser melted thin-walled parts by response surface method

NASA Astrophysics Data System (ADS)

Liu, Yang; Zhang, Jian; Pang, Zhicong; Wu, Weihui

2018-04-01

Selective laser melting (SLM) provides a feasible way for manufacturing of complex thin-walled parts directly, however, the energy input during SLM process, namely derived from the laser power, scanning speed, layer thickness and scanning space, etc. has great influence on the thin wall's qualities. The aim of this work is to relate the thin wall's parameters (responses), namely track width, surface roughness and hardness to the process parameters considered in this research (laser power, scanning speed and layer thickness) and to find out the optimal manufacturing conditions. Design of experiment (DoE) was used by implementing composite central design to achieve better manufacturing qualities. Mathematical models derived from the statistical analysis were used to establish the relationships between the process parameters and the responses. Also, the effects of process parameters on each response were determined. Then, a numerical optimization was performed to find out the optimal process set at which the quality features are at their desired values. Based on this study, the relationship between process parameters and SLMed thin-walled structure was revealed and thus, the corresponding optimal process parameters can be used to manufactured thin-walled parts with high quality.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

NASA Astrophysics Data System (ADS)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that the early spring net primary production could be used to predict parameters affecting the annual methane production. Even though the calibration is specific to the Siikaneva site, the hierarchical modeling approach is well suited for larger-scale studies and the results of the estimation pave way for a regional or global-scale Bayesian calibration of wetland emission models.

Parameter interdependence and uncertainty induced by lumping in a hydrologic model

NASA Astrophysics Data System (ADS)

Gallagher, Mark R.; Doherty, John

2007-05-01

Throughout the world, watershed modeling is undertaken using lumped parameter hydrologic models that represent real-world processes in a manner that is at once abstract, but nevertheless relies on algorithms that reflect real-world processes and parameters that reflect real-world hydraulic properties. In most cases, values are assigned to the parameters of such models through calibration against flows at watershed outlets. One criterion by which the utility of the model and the success of the calibration process are judged is that realistic values are assigned to parameters through this process. This study employs regularization theory to examine the relationship between lumped parameters and corresponding real-world hydraulic properties. It demonstrates that any kind of parameter lumping or averaging can induce a substantial amount of "structural noise," which devices such as Box-Cox transformation of flows and autoregressive moving average (ARMA) modeling of residuals are unlikely to render homoscedastic and uncorrelated. Furthermore, values estimated for lumped parameters are unlikely to represent average values of the hydraulic properties after which they are named and are often contaminated to a greater or lesser degree by the values of hydraulic properties which they do not purport to represent at all. As a result, the question of how rigidly they should be bounded during the parameter estimation process is still an open one.

Model-based analysis of coupled equilibrium-kinetic processes: indirect kinetic studies of thermodynamic parameters using the dynamic data.

PubMed

Emami, Fereshteh; Maeder, Marcel; Abdollahi, Hamid

2015-05-07

Thermodynamic studies of equilibrium chemical reactions linked with kinetic procedures are mostly impossible by traditional approaches. In this work, the new concept of generalized kinetic study of thermodynamic parameters is introduced for dynamic data. The examples of equilibria intertwined with kinetic chemical mechanisms include molecular charge transfer complex formation reactions, pH-dependent degradation of chemical compounds and tautomerization kinetics in micellar solutions. Model-based global analysis with the possibility of calculating and embedding the equilibrium and kinetic parameters into the fitting algorithm has allowed the complete analysis of the complex reaction mechanisms. After the fitting process, the optimal equilibrium and kinetic parameters together with an estimate of their standard deviations have been obtained. This work opens up a promising new avenue for obtaining equilibrium constants through the kinetic data analysis for the kinetic reactions that involve equilibrium processes.

Analysis of the shrinkage at the thick plate part using response surface methodology

NASA Astrophysics Data System (ADS)

Hatta, N. M.; Azlan, M. Z.; Shayfull, Z.; Roselina, S.; Nasir, S. M.

2017-09-01

Injection moulding is well known for its manufacturing process especially in producing plastic products. To measure the final product quality, there are lots of precautions to be taken into such as parameters setting at the initial stage of the process. Sometimes, if these parameters were set up wrongly, defects may be occurred and one of the well-known defects in the injection moulding process is a shrinkage. To overcome this problem, a maximisation at the precaution stage by making an optimal adjustment on the parameter setting need to be done and this paper focuses on analysing the shrinkage by optimising the parameter at thick plate part with the help of Response Surface Methodology (RSM) and ANOVA analysis. From the previous study, the outstanding parameter gained from the optimisation method in minimising the shrinkage at the moulded part was packing pressure. Therefore, with the reference from the previous literature, packing pressure was selected as the parameter setting for this study with other three parameters which are melt temperature, cooling time and mould temperature. The analysis of the process was obtained from the simulation by Autodesk Moldflow Insight (AMI) software and the material used for moulded part was Acrylonitrile Butadiene Styrene (ABS). The analysis and result were obtained and it found that the shrinkage can be minimised and the significant parameters were found as packing pressure, mould temperature and melt temperature.

An Optimized Trajectory Planning for Welding Robot

NASA Astrophysics Data System (ADS)

Chen, Zhilong; Wang, Jun; Li, Shuting; Ren, Jun; Wang, Quan; Cheng, Qunchao; Li, Wentao

2018-03-01

In order to improve the welding efficiency and quality, this paper studies the combined planning between welding parameters and space trajectory for welding robot and proposes a trajectory planning method with high real-time performance, strong controllability and small welding error. By adding the virtual joint at the end-effector, the appropriate virtual joint model is established and the welding process parameters are represented by the virtual joint variables. The trajectory planning is carried out in the robot joint space, which makes the control of the welding process parameters more intuitive and convenient. By using the virtual joint model combined with the B-spline curve affine invariant, the welding process parameters are indirectly controlled by controlling the motion curve of the real joint. To solve the optimal time solution as the goal, the welding process parameters and joint space trajectory joint planning are optimized.

CO 2 laser cutting of MDF . 1. Determination of process parameter settings

NASA Astrophysics Data System (ADS)

Lum, K. C. P.; Ng, S. L.; Black, I.

2000-02-01

This paper details an investigation into the laser processing of medium-density fibreboard (MDF). Part 1 reports on the determination of process parameter settings for the effective cutting of MDF by CO 2 laser, using an established experimental methodology developed to study the interrelationship between and effects of varying laser set-up parameters. Results are presented for both continuous wave (CW) and pulse mode (PM) cutting, and the associated cut quality effects have been commented on.

Disease management programs for type 2 diabetes in Germany: a systematic literature review evaluating effectiveness.

PubMed

Fuchs, Sabine; Henschke, Cornelia; Blümel, Miriam; Busse, Reinhard

2014-06-27

Disease management programs (DMPs) are intended to improve the care of persons with chronic diseases. Despite numerous studies there is no unequivocal evidence about the effectiveness of DMPs in Germany. We conducted a systematic literature review in the MEDLINE, EMBASE, Cochrane Library, and CCMed databases. Our analysis included all controlled studies in which patients with type 2 diabetes enrolled in a DMP were compared to type 2 diabetes patients receiving routine care with respect to process, outcome, and economic parameters. The 9 studies included in the analysis were highly divergent with respect to their characteristics and the process and outcome parameters studied in each. No study had data beyond the year 2008. In 3 publications, the DMP patients had a lower mortality than the control patients (2.3%, 11.3%, and 7.17% versus 4.7%, 14.4%, and 14.72%). In 2 publications, DMP participation was found to be associated with a mean survival time of 1044.94 (± 189.87) days, as against 985.02 (± 264.68) in the control group. No consistent effect was seen with respect to morbidity, quality of life, or economic parameters. 7 publications from 5 studies revealed positive effects on process parameters for DMP participants. The observed beneficial trends with respect to mortality and survival time, as well as improvements in process parameters, indicate that DMPs can, in fact, improve the care of patients with diabetes. Further evaluation is needed, because some changes in outcome parameters (an important indicator of the quality of care) may only be observable over a longer period of time.

A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

USGS Publications Warehouse

Ward, Adam S.; Kelleher, Christa A.; Mason, Seth J. K.; Wagener, Thorsten; McIntyre, Neil; McGlynn, Brian L.; Runkel, Robert L.; Payn, Robert A.

2017-01-01

Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.

Identification of Optimum Magnetic Behavior of NanoCrystalline CmFeAl Type Heusler Alloy Powders Using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Srivastava, Y.; Srivastava, S.; Boriwal, L.

2016-09-01

Mechanical alloying is a novelistic solid state process that has received considerable attention due to many advantages over other conventional processes. In the present work, Co2FeAl healer alloy powder, prepared successfully from premix basic powders of Cobalt (Co), Iron (Fe) and Aluminum (Al) in stoichiometric of 60Co-26Fe-14Al (weight %) by novelistic mechano-chemical route. Magnetic properties of mechanically alloyed powders were characterized by vibrating sample magnetometer (VSM). 2 factor 5 level design matrix was applied to experiment process. Experimental results were used for response surface methodology. Interaction between the input process parameters and the response has been established with the help of regression analysis. Further analysis of variance technique was applied to check the adequacy of developed model and significance of process parameters. Test case study was performed with those parameters, which was not selected for main experimentation but range was same. Response surface methodology, the process parameters must be optimized to obtain improved magnetic properties. Further optimum process parameters were identified using numerical and graphical optimization techniques.

Improving tablet coating robustness by selecting critical process parameters from retrospective data.

PubMed

Galí, A; García-Montoya, E; Ascaso, M; Pérez-Lozano, P; Ticó, J R; Miñarro, M; Suñé-Negre, J M

2016-09-01

Although tablet coating processes are widely used in the pharmaceutical industry, they often lack adequate robustness. Up-scaling can be challenging as minor changes in parameters can lead to varying quality results. To select critical process parameters (CPP) using retrospective data of a commercial product and to establish a design of experiments (DoE) that would improve the robustness of the coating process. A retrospective analysis of data from 36 commercial batches. Batches were selected based on the quality results generated during batch release, some of which revealed quality deviations concerning the appearance of the coated tablets. The product is already marketed and belongs to the portfolio of a multinational pharmaceutical company. The Statgraphics 5.1 software was used for data processing to determine critical process parameters in order to propose new working ranges. This study confirms that it is possible to determine the critical process parameters and create design spaces based on retrospective data of commercial batches. This type of analysis is thus converted into a tool to optimize the robustness of existing processes. Our results show that a design space can be established with minimum investment in experiments, since current commercial batch data are processed statistically.

Dimension scaling effects on the yield sensitivity of HEMT digital circuits

NASA Technical Reports Server (NTRS)

Sarker, Jogendra C.; Purviance, John E.

1992-01-01

In our previous works, using a graphical tool, yield factor histograms, we studied the yield sensitivity of High Electron Mobility Transistors (HEMT) and HEMT circuit performance with the variation of process parameters. This work studies the scaling effects of process parameters on yield sensitivity of HEMT digital circuits. The results from two HEMT circuits are presented.

Application of high-throughput mini-bioreactor system for systematic scale-down modeling, process characterization, and control strategy development.

PubMed

Janakiraman, Vijay; Kwiatkowski, Chris; Kshirsagar, Rashmi; Ryll, Thomas; Huang, Yao-Ming

2015-01-01

High-throughput systems and processes have typically been targeted for process development and optimization in the bioprocessing industry. For process characterization, bench scale bioreactors have been the system of choice. Due to the need for performing different process conditions for multiple process parameters, the process characterization studies typically span several months and are considered time and resource intensive. In this study, we have shown the application of a high-throughput mini-bioreactor system viz. the Advanced Microscale Bioreactor (ambr15(TM) ), to perform process characterization in less than a month and develop an input control strategy. As a pre-requisite to process characterization, a scale-down model was first developed in the ambr system (15 mL) using statistical multivariate analysis techniques that showed comparability with both manufacturing scale (15,000 L) and bench scale (5 L). Volumetric sparge rates were matched between ambr and manufacturing scale, and the ambr process matched the pCO2 profiles as well as several other process and product quality parameters. The scale-down model was used to perform the process characterization DoE study and product quality results were generated. Upon comparison with DoE data from the bench scale bioreactors, similar effects of process parameters on process yield and product quality were identified between the two systems. We used the ambr data for setting action limits for the critical controlled parameters (CCPs), which were comparable to those from bench scale bioreactor data. In other words, the current work shows that the ambr15(TM) system is capable of replacing the bench scale bioreactor system for routine process development and process characterization. © 2015 American Institute of Chemical Engineers.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

PubMed

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

PubMed Central

2010-01-01

Background Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. Results In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. Conclusions The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates. PMID:20500862

Analysing the influence of FSP process parameters on IGC susceptibility of AA5083 using Sugeno - Fuzzy model

NASA Astrophysics Data System (ADS)

Jayakarthick, C.; Povendhan, A. P.; Vaira Vignesh, R.; Padmanaban, R.

2018-02-01

Aluminium alloy AA5083 was friction stir processed to improve the intergranular corrosion (IGC) resistance. FSP trials were performed by varying the process parameters as per Taguchi’s L18 orthogonal array. IGC resistance of the friction stir processed specimens were found by immersing them in concentrated nitric acid and measuring the mass loss per unit area. Results indicate that dispersion and partial dissolution of secondary phase increased IGC resistance of the friction stir processed specimens. A Sugeno fuzzy model was developed to study the effect of FSP process parameters on the IGC susceptibility of friction stir processed specimens. Tool Rotation Speed, Tool Traverse Speed and Shoulder Diameter have a significant effect on the IGC susceptibility of the friction stir processed specimens.

Optimisation of shock absorber process parameters using failure mode and effect analysis and genetic algorithm

NASA Astrophysics Data System (ADS)

Mariajayaprakash, Arokiasamy; Senthilvelan, Thiyagarajan; Vivekananthan, Krishnapillai Ponnambal

2013-07-01

The various process parameters affecting the quality characteristics of the shock absorber during the process were identified using the Ishikawa diagram and by failure mode and effect analysis. The identified process parameters are welding process parameters (squeeze, heat control, wheel speed, and air pressure), damper sealing process parameters (load, hydraulic pressure, air pressure, and fixture height), washing process parameters (total alkalinity, temperature, pH value of rinsing water, and timing), and painting process parameters (flowability, coating thickness, pointage, and temperature). In this paper, the process parameters, namely, painting and washing process parameters, are optimized by Taguchi method. Though the defects are reasonably minimized by Taguchi method, in order to achieve zero defects during the processes, genetic algorithm technique is applied on the optimized parameters obtained by Taguchi method.

Regarding to the Variance Analysis of Regression Equation of the Surface Roughness obtained by End Milling process of 7136 Aluminium Alloy

NASA Astrophysics Data System (ADS)

POP, A. B.; ȚÎȚU, M. A.

2016-11-01

In the metal cutting process, surface quality is intrinsically related to the cutting parameters and to the cutting tool geometry. At the same time, metal cutting processes are closely related to the machining costs. The purpose of this paper is to reduce manufacturing costs and processing time. A study was made, based on the mathematical modelling of the average of the absolute value deviation (Ra) resulting from the end milling process on 7136 aluminium alloy, depending on cutting process parameters. The novel element brought by this paper is the 7136 aluminium alloy type, chosen to conduct the experiments, which is a material developed and patented by Universal Alloy Corporation. This aluminium alloy is used in the aircraft industry to make parts from extruded profiles, and it has not been studied for the proposed research direction. Based on this research, a mathematical model of surface roughness Ra was established according to the cutting parameters studied in a set experimental field. A regression analysis was performed, which identified the quantitative relationships between cutting parameters and the surface roughness. Using the variance analysis ANOVA, the degree of confidence for the achieved results by the regression equation was determined, and the suitability of this equation at every point of the experimental field.

Effects of the Deslagging Process on some Physicochemical Parameters of Honey

PubMed Central

Ranjbar, Ali Mohammad; Sadeghpour, Omid; Khanavi, Mahnaz; Shams Ardekani, Mohammad Reza; Moloudian, Hamid; Hajimahmoodi, Mannan

2015-01-01

Some physicochemical parameters of honey have been introduced by the International Honey Commission to evaluate its quality and origin but processes such as heating and filtering can affect these parameters. In traditional Iranian medicine, deslagging process involves boiling honey in an equal volume of water and removing the slag formed during process. The aim of this study was to determine the effects of deslagging process on parameters of color intensity, diastase evaluation, electrical conductivity, pH, free acidity, refractive index, hydroxy methyl furfural (HMF), proline and water contents according to the International Honey Committee (IHC) standards. The results showed that deslagged honey was significantly different from control honey in terms of color intensity, pH, diastase number, HMF and proline content. It can be concluded that the new standards are needed to regulate deslagged honey. PMID:25901175

Effects of process parameters on the molding quality of the micro-needle array

NASA Astrophysics Data System (ADS)

Qiu, Z. J.; Ma, Z.; Gao, S.

2016-07-01

Micro-needle array, which is used in medical applications, is a kind of typical injection molded products with microstructures. Due to its tiny micro-features size and high aspect ratios, it is more likely to produce short shots defects, leading to poor molding quality. The injection molding process of the micro-needle array was studied in this paper to find the effects of the process parameters on the molding quality of the micro-needle array and to provide theoretical guidance for practical production of high-quality products. With the shrinkage ratio and warpage of micro needles as the evaluation indices of the molding quality, the orthogonal experiment was conducted and the analysis of variance was carried out. According to the results, the contribution rates were calculated to determine the influence of various process parameters on molding quality. The single parameter method was used to analyse the main process parameter. It was found that the contribution rate of the holding pressure on shrinkage ratio and warpage reached 83.55% and 94.71% respectively, far higher than that of the other parameters. The study revealed that the holding pressure is the main factor which affects the molding quality of micro-needle array so that it should be focused on in order to obtain plastic parts with high quality in the practical production.

Experimental Research on Selective Laser Melting AlSi10Mg Alloys: Process, Densification and Performance

NASA Astrophysics Data System (ADS)

Chen, Zhen; Wei, Zhengying; Wei, Pei; Chen, Shenggui; Lu, Bingheng; Du, Jun; Li, Junfeng; Zhang, Shuzhe

2017-12-01

In this work, a set of experiments was designed to investigate the effect of process parameters on the relative density of the AlSi10Mg parts manufactured by SLM. The influence of laser scan speed v, laser power P and hatch space H, which were considered as the dominant parameters, on the powder melting and densification behavior was also studied experimentally. In addition, the laser energy density was introduced to evaluate the combined effect of the above dominant parameters, so as to control the SLM process integrally. As a result, a high relative density (> 97%) was obtained by SLM at an optimized laser energy density of 3.5-5.5 J/mm2. Moreover, a parameter-densification map was established to visually select the optimum process parameters for the SLM-processed AlSi10Mg parts with elevated density and required mechanical properties. The results provide an important experimental guidance for obtaining AlSi10Mg components with full density and gradient functional porosity by SLM.

Optimization of hybrid laser - TIG welding of 316LN steel using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Ragavendran, M.; Chandrasekhar, N.; Ravikumar, R.; Saxena, Rajesh; Vasudevan, M.; Bhaduri, A. K.

2017-07-01

In the present study, the hybrid laser - TIG welding parameters for welding of 316LN austenitic stainless steel have been investigated by combining a pulsed laser beam with a TIG welding heat source at the weld pool. Laser power, pulse frequency, pulse duration, TIG current were presumed as the welding process parameters whereas weld bead width, weld cross-sectional area and depth of penetration (DOP) were considered as the process responses. Central composite design was used to complete the design matrix and welding experiments were conducted based on the design matrix. Weld bead measurements were then carried out to generate the dataset. Multiple regression models correlating the process parameters with the responses have been developed. The accuracy of the models were found to be good. Then, the desirability approach optimization technique was employed for determining the optimum process parameters to obtain the desired weld bead profile. Validation experiments were then carried out from the determined optimum process parameters. There was good agreement between the predicted and measured values.

The physicochemical process of bacterial attachment to abiotic surfaces: Challenges for mechanistic studies, predictability and the development of control strategies.

PubMed

Wang, Yi; Lee, Sui Mae; Dykes, Gary

2015-01-01

Bacterial attachment to abiotic surfaces can be explained as a physicochemical process. Mechanisms of the process have been widely studied but are not yet well understood due to their complexity. Physicochemical processes can be influenced by various interactions and factors in attachment systems, including, but not limited to, hydrophobic interactions, electrostatic interactions and substratum surface roughness. Mechanistic models and control strategies for bacterial attachment to abiotic surfaces have been established based on the current understanding of the attachment process and the interactions involved. Due to a lack of process control and standardization in the methodologies used to study the mechanisms of bacterial attachment, however, various challenges are apparent in the development of models and control strategies. In this review, the physicochemical mechanisms, interactions and factors affecting the process of bacterial attachment to abiotic surfaces are described. Mechanistic models established based on these parameters are discussed in terms of their limitations. Currently employed methods to study these parameters and bacterial attachment are critically compared. The roles of these parameters in the development of control strategies for bacterial attachment are reviewed, and the challenges that arise in developing mechanistic models and control strategies are assessed.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Optimisation of warpage on plastic injection moulding part using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Miza, A. T. N. A.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Rashidi, M. M.

2017-09-01

The warpage is often encountered which occur during injection moulding process of thin shell part depending the process condition. The statistical design of experiment method which are Integrating Finite Element (FE) Analysis, moldflow analysis and response surface methodology (RSM) are the stage of few ways in minimize the warpage values of x,y and z on thin shell plastic parts that were investigated. A battery cover of a remote controller is one of the thin shell plastic part that produced by using injection moulding process. The optimum process condition parameter were determined as to achieve the minimum warpage from being occur. Packing pressure, Cooling time, Melt temperature and Mould temperature are 4 parameters that considered in this study. A two full factorial experimental design was conducted in Design Expert of RSM analysis as to combine all these parameters study. FE analysis result gain from analysis of variance (ANOVA) method was the one of the important process parameters influenced warpage. By using RSM, a predictive response surface model for warpage data will be shown.

Effect of simultaneous infrared dry-blanching and dehydration on quality characteristics of carrot slices

USDA-ARS?s Scientific Manuscript database

This study investigated the effects of various processing parameters on carrot slices exposed to infrared (IR) radiation heating for achieving simultaneous infrared dry-blanching and dehydration (SIRDBD). The investigated parameters were product surface temperature, slice thickness and processing ti...

Wind speed vector restoration algorithm

NASA Astrophysics Data System (ADS)

Baranov, Nikolay; Petrov, Gleb; Shiriaev, Ilia

2018-04-01

Impulse wind lidar (IWL) signal processing software developed by JSC «BANS» recovers full wind speed vector by radial projections and provides wind parameters information up to 2 km distance. Increasing accuracy and speed of wind parameters calculation signal processing technics have been studied in this research. Measurements results of IWL and continuous scanning lidar were compared. Also, IWL data processing modeling results have been analyzed.

Catchment process affecting drinking water quality, including the significance of rainfall events, using factor analysis and event mean concentrations.

PubMed

Cinque, Kathy; Jayasuriya, Niranjali

2010-12-01

To ensure the protection of drinking water an understanding of the catchment processes which can affect water quality is important as it enables targeted catchment management actions to be implemented. In this study factor analysis (FA) and comparing event mean concentrations (EMCs) with baseline values were techniques used to asses the relationships between water quality parameters and linking those parameters to processes within an agricultural drinking water catchment. FA found that 55% of the variance in the water quality data could be explained by the first factor, which was dominated by parameters usually associated with erosion. Inclusion of pathogenic indicators in an additional FA showed that Enterococcus and Clostridium perfringens (C. perfringens) were also related to the erosion factor. Analysis of the EMCs found that most parameters were significantly higher during periods of rainfall runoff. This study shows that the most dominant processes in an agricultural catchment are surface runoff and erosion. It also shows that it is these processes which mobilise pathogenic indicators and are therefore most likely to influence the transport of pathogens. Catchment management efforts need to focus on reducing the effect of these processes on water quality.

Parameter Design in Fusion Welding of AA 6061 Aluminium Alloy using Desirability Grey Relational Analysis (DGRA) Method

NASA Astrophysics Data System (ADS)

Adalarasan, R.; Santhanakumar, M.

2015-01-01

In the present work, yield strength, ultimate strength and micro-hardness of the lap joints formed with Al 6061 alloy sheets by using the processes of Tungsten Inert Gas (TIG) welding and Metal Inert Gas (MIG) welding were studied for various combinations of the welding parameters. The parameters taken for study include welding current, voltage, welding speed and inert gas flow rate. Taguchi's L9 orthogonal array was used to conduct the experiments and an integrated technique of desirability grey relational analysis was disclosed for optimizing the welding parameters. The ignored robustness in desirability approach is compensated by the grey relational approach to predict the optimal setting of input parameters for the TIG and MIG welding processes which were validated through the confirmation experiments.

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Little, K; Lu, Z; MacMahon, H

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, whichmore » were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.« less

Quantifying the impact of the longitudinal dispersion coefficient parameter uncertainty on the physical transport processes in rivers

NASA Astrophysics Data System (ADS)

Camacho Suarez, V. V.; Shucksmith, J.; Schellart, A.

2016-12-01

Analytical and numerical models can be used to represent the advection-dispersion processes governing the transport of pollutants in rivers (Fan et al., 2015; Van Genuchten et al., 2013). Simplifications, assumptions and parameter estimations in these models result in various uncertainties within the modelling process and estimations of pollutant concentrations. In this study, we explore both: 1) the structural uncertainty due to the one dimensional simplification of the Advection Dispersion Equation (ADE) and 2) the parameter uncertainty due to the semi empirical estimation of the longitudinal dispersion coefficient. The relative significance of these uncertainties has not previously been examined. By analysing both the relative structural uncertainty of analytical solutions of the ADE, and the parameter uncertainty due to the longitudinal dispersion coefficient via a Monte Carlo analysis, an evaluation of the dominant uncertainties for a case study in the river Chillan, Chile is presented over a range of spatial scales.

Effect of processing parameters on the corrosion behaviour of friction stir processed AA 2219 aluminum alloy

NASA Astrophysics Data System (ADS)

Surekha, K.; Murty, B. S.; Prasad Rao, K.

2009-04-01

The effect of processing parameters (rotation speed and traverse speed) on the corrosion behaviour of friction stir processed high strength precipitation hardenable AA 2219-T87 alloy was investigated. The results indicate that the rotation speed has a major influence in determining the rate of corrosion, which is attributed to the breaking down and dissolution of the intermetallic particles. Corrosion resistance of friction stir processed alloy was studied by potentiodynamic polarization, electrochemical impedance spectroscopy, salt spray and immersion tests.

A Computational Study on Porosity Evolution in Parts Produced by Selective Laser Melting

NASA Astrophysics Data System (ADS)

Tan, J. L.; Tang, C.; Wong, C. H.

2018-06-01

Selective laser melting (SLM) is a powder-bed additive manufacturing process that uses laser to melt powders, layer by layer to generate a functional 3D part. There are many different parameters, such as laser power, scanning speed, and layer thickness, which play a role in determining the quality of the printed part. These parameters contribute to the energy density applied on the powder bed. Defects arise when insufficient or excess energy density is applied. A common defect in these cases is the presence of porosity. This paper studies the formation of porosities when inappropriate energy densities are used. A computational model was developed to simulate the melting and solidification process of SS316L powders in the SLM process. Three different sets of process parameters were used to produce 800-µm-long melt tracks, and the characteristics of the porosities were analyzed. It was found that when low energy density parameters were used, the pores were found to be irregular in shapes and were located near the top surface of the powder bed. However, when high energy density parameters were used, the pores were either elliptical or spherical in shapes and were usually located near the bottom of the keyholes.

TEM study of the FSW nugget in AA2195-T81

NASA Technical Reports Server (NTRS)

Schneider, J. A.; Nunes, A. C., Jr.; Chen, P. S.; Steele, G.

2004-01-01

During fiiction stir welding (FSW) the material being joined is subjected to a thermal- mechanical process in which the temperature, strain and strain rates are not completely understood. To produce a defect fiee weld, process parameters for the weld and tool pin design must be chosen carefully. The ability to select the weld parameters based on the thermal processing requirements of the material, would allow optimization of mechanical properties in the weld region. In this study, an attempt is made to correlate the microstructure with the variation in thermal history the material experiences during the FSW process.

The Taguchi Method Application to Improve the Quality of a Sustainable Process

NASA Astrophysics Data System (ADS)

Titu, A. M.; Sandu, A. V.; Pop, A. B.; Titu, S.; Ciungu, T. C.

2018-06-01

Taguchi’s method has always been a method used to improve the quality of the analyzed processes and products. This research shows an unusual situation, namely the modeling of some parameters, considered technical parameters, in a process that is wanted to be durable by improving the quality process and by ensuring quality using an experimental research method. Modern experimental techniques can be applied in any field and this study reflects the benefits of interacting between the agriculture sustainability principles and the Taguchi’s Method application. The experimental method used in this practical study consists of combining engineering techniques with experimental statistical modeling to achieve rapid improvement of quality costs, in fact seeking optimization at the level of existing processes and the main technical parameters. The paper is actually a purely technical research that promotes a technical experiment using the Taguchi method, considered to be an effective method since it allows for rapid achievement of 70 to 90% of the desired optimization of the technical parameters. The missing 10 to 30 percent can be obtained with one or two complementary experiments, limited to 2 to 4 technical parameters that are considered to be the most influential. Applying the Taguchi’s Method in the technique and not only, allowed the simultaneous study in the same experiment of the influence factors considered to be the most important in different combinations and, at the same time, determining each factor contribution.

Optimization of process parameters for a quasi-continuous tablet coating system using design of experiments.

PubMed

Cahyadi, Christine; Heng, Paul Wan Sia; Chan, Lai Wah

2011-03-01

The aim of this study was to identify and optimize the critical process parameters of the newly developed Supercell quasi-continuous coater for optimal tablet coat quality. Design of experiments, aided by multivariate analysis techniques, was used to quantify the effects of various coating process conditions and their interactions on the quality of film-coated tablets. The process parameters varied included batch size, inlet temperature, atomizing pressure, plenum pressure, spray rate and coating level. An initial screening stage was carried out using a 2(6-1(IV)) fractional factorial design. Following these preliminary experiments, optimization study was carried out using the Box-Behnken design. Main response variables measured included drug-loading efficiency, coat thickness variation, and the extent of tablet damage. Apparent optimum conditions were determined by using response surface plots. The process parameters exerted various effects on the different response variables. Hence, trade-offs between individual optima were necessary to obtain the best compromised set of conditions. The adequacy of the optimized process conditions in meeting the combined goals for all responses was indicated by the composite desirability value. By using response surface methodology and optimization, coating conditions which produced coated tablets of high drug-loading efficiency, low incidences of tablet damage and low coat thickness variation were defined. Optimal conditions were found to vary over a large spectrum when different responses were considered. Changes in processing parameters across the design space did not result in drastic changes to coat quality, thereby demonstrating robustness in the Supercell coating process. © 2010 American Association of Pharmaceutical Scientists

Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

NASA Astrophysics Data System (ADS)

Kumar, S.; Singh, A.; Dhar, A.

2017-08-01

The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.

Evaluating the process parameters of the dry coating process using a 2(5-1) factorial design.

PubMed

Kablitz, Caroline Désirée; Urbanetz, Nora Anne

2013-02-01

A recent development of coating technology is dry coating, where polymer powder and liquid plasticizer are layered on the cores without using organic solvents or water. Several studies evaluating the process were introduced in literature, however, little information about the critical process parameters (CPPs) is given. Aim of the study was the investigation and optimization of CPPs with respect to one of the critical quality attributes (CQAs), the coating efficiency of the dry coating process in a rotary fluid bed. Theophylline pellets were coated with hydroxypropyl methylcellulose acetate succinate as enteric film former and triethyl citrate and acetylated monoglyceride as plasticizer. A 2(5-1) design of experiments (DOEs) was created investigating five independent process parameters namely coating temperature, curing temperature, feeding/spraying rate, air flow and rotor speed. The results were evaluated by multilinear regression using the software Modde(®) 7. It is shown, that generally, low feeding/spraying rates and low rotor speeds increase coating efficiency. High coating temperatures enhance coating efficiency, whereas medium curing temperatures have been found to be optimum in terms of coating efficiency. This study provides a scientific base for the design of efficient dry coating processes with respect to coating efficiency.

Effects of process parameters in plastic, metal, and ceramic injection molding processes

NASA Astrophysics Data System (ADS)

Lee, Shi W.; Ahn, Seokyoung; Whang, Chul Jin; Park, Seong Jin; Atre, Sundar V.; Kim, Jookwon; German, Randall M.

2011-09-01

Plastic injection molding has been widely used in the past and is a dominant forming approach today. As the customer demands require materials with better engineering properties that were not feasible with polymers, powder injection molding with metal and ceramic powders has received considerable attention in recent decades. To better understand the differences in the plastic injection molding, metal injection molding, and ceramic injection molding, the effects of the core process parameters on the process performances has been studied using the state-of-the-art computer-aided engineering (CAE) design tool, PIMSolver® The design of experiments has been conducted using the Taguchi method to obtain the relative contributions of various process parameters onto the successful operations.

Effect of Laser Power and Gas Flow Rate on Properties of Directed Energy Deposition of Titanium Alloy

NASA Astrophysics Data System (ADS)

Mahamood, Rasheedat M.

2018-03-01

Laser metal deposition (LMD) process belongs to the directed energy deposition class of additive manufacturing processes. It is an important manufacturing technology with lots of potentials especially for the automobile and aerospace industries. The laser metal deposition process is fairly new, and the process is very sensitive to the processing parameters. There is a high level of interactions among these process parameters. The surface finish of part produced using the laser metal deposition process is dependent on the processing parameters. Also, the economy of the LMD process depends largely on steps taken to eliminate or reduce the need for secondary finishing operations. In this study, the influence of laser power and gas flow rate on the microstructure, microhardness and surface finish produced during the laser metal deposition of Ti6Al4V was investigated. The laser power was varied between 1.8 kW and 3.0 kW, while the gas flow rate was varied between 2 l/min and 4 l/min. The microstructure was studied under an optical microscope, the microhardness was studied using a Metkon microhardness indenter, while the surface roughness was studied using a Jenoptik stylus surface analyzer. The results showed that better surface finish was produced at a laser power of 3.0 kW and a gas flow rate of 4 l/min.

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez, A; Little, K; Chung, J

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidencemore » of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.« less

Effects of Processing Parameters on the Forming Quality of C-Shaped Thermosetting Composite Laminates in Hot Diaphragm Forming Process

NASA Astrophysics Data System (ADS)

Bian, X. X.; Gu, Y. Z.; Sun, J.; Li, M.; Liu, W. P.; Zhang, Z. G.

2013-10-01

In this study, the effects of processing temperature and vacuum applying rate on the forming quality of C-shaped carbon fiber reinforced epoxy resin matrix composite laminates during hot diaphragm forming process were investigated. C-shaped prepreg preforms were produced using a home-made hot diaphragm forming equipment. The thickness variations of the preforms and the manufacturing defects after diaphragm forming process, including fiber wrinkling and voids, were evaluated to understand the forming mechanism. Furthermore, both interlaminar slipping friction and compaction behavior of the prepreg stacks were experimentally analyzed for showing the importance of the processing parameters. In addition, autoclave processing was used to cure the C-shaped preforms to investigate the changes of the defects before and after cure process. The results show that the C-shaped prepreg preforms with good forming quality can be achieved through increasing processing temperature and reducing vacuum applying rate, which obviously promote prepreg interlaminar slipping process. The process temperature and forming rate in hot diaphragm forming process strongly influence prepreg interply frictional force, and the maximum interlaminar frictional force can be taken as a key parameter for processing parameter optimization. Autoclave process is effective in eliminating voids in the preforms and can alleviate fiber wrinkles to a certain extent.

Multi-objective optimization of process parameters of multi-step shaft formed with cross wedge rolling based on orthogonal test

NASA Astrophysics Data System (ADS)

Han, S. T.; Shu, X. D.; Shchukin, V.; Kozhevnikova, G.

2018-06-01

In order to achieve reasonable process parameters in forming multi-step shaft by cross wedge rolling, the research studied the rolling-forming process multi-step shaft on the DEFORM-3D finite element software. The interactive orthogonal experiment was used to study the effect of the eight parameters, the first section shrinkage rate φ1, the first forming angle α1, the first spreading angle β1, the first spreading length L1, the second section shrinkage rate φ2, the second forming angle α2, the second spreading angle β2 and the second spreading length L2, on the quality of shaft end and the microstructure uniformity. By using the fuzzy mathematics comprehensive evaluation method and the extreme difference analysis, the influence degree of the process parameters on the quality of the multi-step shaft is obtained: β2>φ2L1>α1>β1>φ1>α2L2. The results of the study can provide guidance for obtaining multi-stepped shaft with high mechanical properties and achieving near net forming without stub bar in cross wedge rolling.

Study of parameters in precision optical glass molding

NASA Astrophysics Data System (ADS)

Ni, Ying; Wang, Qin-hua; Yu, Jing-chi

2010-10-01

Precision glass compression molding is an attractive approach to manufacture small precision optics in large volume over traditional manufacturing techniques because of its advantages such as lower cost, faster time to market and being environment friendly. In order to study the relationship between the surface figures of molded lenses and molding process parameters such as temperature, pressure, heating rate, cooling rate and so on, we present some glass compression molding experiments using same low Tg (transition temperature) glass material to produce two different kinds of aspheric lenses by different molding process parameters. Based on results from the experiments, we know the major factors influencing surface figure of molded lenses and the changing range of these parameters. From the knowledge we could easily catch proper molding parameters which are suitable for aspheric lenses with diameter from 10mm to 30mm.

Thermodynamic Behavior Research Analysis of Twin-roll Casting Lead Alloy Strip Process

NASA Astrophysics Data System (ADS)

Jiang, Chengcan; Rui, Yannian

2017-03-01

The thermodynamic behavior of twin-roll casting (TRC) lead alloy strip process directly affects the forming of the lead strip, the quality of the lead strip and the production efficiency. However, there is little research on the thermodynamics of lead alloy strip at home and abroad. The TRC lead process is studied in four parameters: the pouring temperature of molten lead, the depth of molten pool, the roll casting speed, and the rolling thickness of continuous casting. Firstly, the thermodynamic model for TRC lead process is built. Secondly, the thermodynamic behavior of the TRC process is simulated with the use of Fluent. Through the thermodynamics research and analysis, the process parameters of cast rolling lead strip can be obtained: the pouring temperature of molten lead: 360-400 °C, the depth of molten pool: 250-300 mm, the roll casting speed: 2.5-3 m/min, the rolling thickness: 8-9 mm. Based on the above process parameters, the optimal parameters(the pouring temperature of molten lead: 375-390 °C, the depth of molten pool: 285-300 mm, the roll casting speed: 2.75-3 m/min, the rolling thickness: 8.5-9 mm) can be gained with the use of the orthogonal experiment. Finally, the engineering test of TRC lead alloy strip is carried out and the test proves the thermodynamic model is scientific, necessary and correct. In this paper, a detailed study on the thermodynamic behavior of lead alloy strip is carried out and the process parameters of lead strip forming are obtained through the research, which provide an effective theoretical guide for TRC lead alloy strip process.

Investigation of selected structural parameters in Fe 95Si 5 amorphous alloy during crystallization process

NASA Astrophysics Data System (ADS)

Fronczyk, Adam

2007-04-01

In this study, we report on a crystallization behavior of the Fe 95Si 5 metallic glasses using a differential scanning cabrimetry (DSC), and X-ray diffraction. The paper presents the results of experimental investigation of Fe 95Si 5 amorphous alloy, subjected to the crystallizing process by the isothermal annealing. The objective of the experiment was to determine changes in the structural parameters during crystallization process of the examined alloy. Crystalline diameter and the lattice constant of the crystallizing phase were used as parameters to evaluate structural changes in material.

Process Development of Porcelain Ceramic Material with Binder Jetting Process for Dental Applications

NASA Astrophysics Data System (ADS)

Miyanaji, Hadi; Zhang, Shanshan; Lassell, Austin; Zandinejad, Amirali; Yang, Li

2016-03-01

Custom ceramic structures possess significant potentials in many applications such as dentistry and aerospace where extreme environments are present. Specifically, highly customized geometries with adequate performance are needed for various dental prostheses applications. This paper demonstrates the development of process and post-process parameters for a dental porcelain ceramic material using binder jetting additive manufacturing (AM). Various process parameters such as binder amount, drying power level, drying time and powder spread speed were studied experimentally for their effect on geometrical and mechanical characteristics of green parts. In addition, the effects of sintering and printing parameters on the qualities of the densified ceramic structures were also investigated experimentally. The results provide insights into the process-property relationships for the binder jetting AM process, and some of the challenges of the process that need to be further characterized for the successful adoption of the binder jetting technology in high quality ceramic fabrications are discussed.

Software and Hardware System for Fast Processes Study When Preparing Foundation Beds of Oil and Gas Facilities

NASA Astrophysics Data System (ADS)

Gruzin, A. V.; Gruzin, V. V.; Shalay, V. V.

2018-04-01

Analysis of existing technologies for preparing foundation beds of oil and gas buildings and structures has revealed the lack of reasoned recommendations on the selection of rational technical and technological parameters of compaction. To study the nature of the dynamics of fast processes during compaction of foundation beds of oil and gas facilities, a specialized software and hardware system was developed. The method of calculating the basic technical parameters of the equipment for recording fast processes is presented, as well as the algorithm for processing the experimental data. The performed preliminary studies confirmed the accuracy of the decisions made and the calculations performed.

Computer-Assisted Sperm Analysis (CASA) parameters and their evolution during preparation as predictors of pregnancy in intrauterine insemination with frozen-thawed donor semen cycles.

PubMed

Fréour, Thomas; Jean, Miguel; Mirallié, Sophie; Dubourdieu, Sophie; Barrière, Paul

2010-04-01

To study the potential of CASA parameters in frozen-thawed donor semen before and after preparation on silica gradient as predictors of pregnancy in IUI with donor semen cycles. CASA parameters were measured in thawed donor semen before and after preparation on a silica gradient in 132 couples undergoing 168 IUI cycles with donor semen. The evolution of these parameters throughout this process was calculated. The relationship with cycle outcome was then studied. Clinical pregnancy rate was 18.4% per cycle. CASA parameters on donor semen before or after preparation were not significantly different between pregnancy and failure groups. However, amplitude of lateral head displacement (ALH) of spermatozoa improved in all cycles where pregnancy occurred, thus predicting pregnancy with a sensitivity of 100% and a specificity of 20%. Even if CASA parameters do not seem to predict pregnancy in IUI with donor semen cycles, their evolution during the preparation process should be evaluated, especially for ALH. However, the link between ALH improvement during preparation process and pregnancy remains to be explored. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion

PubMed Central

Sun, Fuqiang; Liu, Le; Li, Xiaoyang; Liao, Haitao

2016-01-01

Accelerated degradation testing (ADT) is an efficient technique for evaluating the lifetime of a highly reliable product whose underlying failure process may be traced by the degradation of the product’s performance parameters with time. However, most research on ADT mainly focuses on a single performance parameter. In reality, the performance of a modern product is usually characterized by multiple parameters, and the degradation paths are usually nonlinear. To address such problems, this paper develops a new s-dependent nonlinear ADT model for products with multiple performance parameters using a general Wiener process and copulas. The general Wiener process models the nonlinear ADT data, and the dependency among different degradation measures is analyzed using the copula method. An engineering case study on a tuner’s ADT data is conducted to demonstrate the effectiveness of the proposed method. The results illustrate that the proposed method is quite effective in estimating the lifetime of a product with s-dependent performance parameters. PMID:27509499

Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion.

PubMed

Sun, Fuqiang; Liu, Le; Li, Xiaoyang; Liao, Haitao

2016-08-06

Accelerated degradation testing (ADT) is an efficient technique for evaluating the lifetime of a highly reliable product whose underlying failure process may be traced by the degradation of the product's performance parameters with time. However, most research on ADT mainly focuses on a single performance parameter. In reality, the performance of a modern product is usually characterized by multiple parameters, and the degradation paths are usually nonlinear. To address such problems, this paper develops a new s-dependent nonlinear ADT model for products with multiple performance parameters using a general Wiener process and copulas. The general Wiener process models the nonlinear ADT data, and the dependency among different degradation measures is analyzed using the copula method. An engineering case study on a tuner's ADT data is conducted to demonstrate the effectiveness of the proposed method. The results illustrate that the proposed method is quite effective in estimating the lifetime of a product with s-dependent performance parameters.

Estimation of fundamental kinetic parameters of polyhydroxybutyrate fermentation process of Azohydromonas australica using statistical approach of media optimization.

PubMed

Gahlawat, Geeta; Srivastava, Ashok K

2012-11-01

Polyhydroxybutyrate or PHB is a biodegradable and biocompatible thermoplastic with many interesting applications in medicine, food packaging, and tissue engineering materials. The present study deals with the enhanced production of PHB by Azohydromonas australica using sucrose and the estimation of fundamental kinetic parameters of PHB fermentation process. The preliminary culture growth inhibition studies were followed by statistical optimization of medium recipe using response surface methodology to increase the PHB production. Later on batch cultivation in a 7-L bioreactor was attempted using optimum concentration of medium components (process variables) obtained from statistical design to identify the batch growth and product kinetics parameters of PHB fermentation. A. australica exhibited a maximum biomass and PHB concentration of 8.71 and 6.24 g/L, respectively in bioreactor with an overall PHB production rate of 0.75 g/h. Bioreactor cultivation studies demonstrated that the specific biomass and PHB yield on sucrose was 0.37 and 0.29 g/g, respectively. The kinetic parameters obtained in the present investigation would be used in the development of a batch kinetic mathematical model for PHB production which will serve as launching pad for further process optimization studies, e.g., design of several bioreactor cultivation strategies to further enhance the biopolymer production.

Research on the processing technology of elongated holes based on rotary ultrasonic drilling

NASA Astrophysics Data System (ADS)

Tong, Yi; Chen, Jianhua; Sun, Lipeng; Yu, Xin; Wang, Xin

2014-08-01

The optical glass is hard, brittle and difficult to process. Based on the method of rotating ultrasonic drilling, the study of single factor on drilling elongated holes was made in optical glass. The processing equipment was DAMA ultrasonic machine, and the machining tools were electroplated with diamond. Through the detection and analysis on the processing quality and surface roughness, the process parameters (the spindle speed, amplitude, feed rate) of rotary ultrasonic drilling were researched, and the influence of processing parameters on surface roughness was obtained, which will provide reference and basis for the actual processing.

Impact parameter sensitive study of inner-shell atomic processes in the experimental storage ring

NASA Astrophysics Data System (ADS)

Gumberidze, A.; Kozhuharov, C.; Zhang, R. T.; Trotsenko, S.; Kozhedub, Y. S.; DuBois, R. D.; Beyer, H. F.; Blumenhagen, K.-H.; Brandau, C.; Bräuning-Demian, A.; Chen, W.; Forstner, O.; Gao, B.; Gassner, T.; Grisenti, R. E.; Hagmann, S.; Hillenbrand, P.-M.; Indelicato, P.; Kumar, A.; Lestinsky, M.; Litvinov, Yu. A.; Petridis, N.; Schury, D.; Spillmann, U.; Trageser, C.; Trassinelli, M.; Tu, X.; Stöhlker, Th.

2017-10-01

In this work, we present a pilot experiment in the experimental storage ring (ESR) at GSI devoted to impact parameter sensitive studies of inner shell atomic processes for low-energy (heavy-) ion-atom collisions. The experiment was performed with bare and He-like xenon ions (Xe54+, Xe52+) colliding with neutral xenon gas atoms, resulting in a symmetric collision system. This choice of the projectile charge states was made in order to compare the effect of a filled K-shell with the empty one. The projectile and target X-rays have been measured at different observation angles for all impact parameters as well as for the impact parameter range of ∼35-70 fm.

Electrochemical reduction of CerMet fuels for transmutation using surrogate CeO2-Mo pellets

NASA Astrophysics Data System (ADS)

Claux, B.; Souček, P.; Malmbeck, R.; Rodrigues, A.; Glatz, J.-P.

2017-08-01

One of the concepts chosen for the transmutation of minor actinides in Accelerator Driven Systems or fast reactors proposes the use of fuels and targets containing minor actinides oxides embedded in an inert matrix either composed of molybdenum metal (CerMet fuel) or of ceramic magnesium oxide (CerCer fuel). Since the sufficient transmutation cannot be achieved in a single step, it requires multi-recycling of the fuel including recovery of the not transmuted minor actinides. In the present work, a pyrochemical process for treatment of Mo metal inert matrix based CerMet fuels is studied, particularly the electroreduction in molten chloride salt as a head-end step required prior the main separation process. At the initial stage, different inactive pellets simulating the fuel containing CeO2 as minor actinide surrogates were examined. The main studied parameters of the process efficiency were the porosity and composition of the pellets and the process parameters as current density and passed charge. The results indicated the feasibility of the process, gave insight into its limiting parameters and defined the parameters for the future experiment on minor actinide containing material.

Effect of processing parameters on surface finish for fused deposition machinable wax patterns

NASA Technical Reports Server (NTRS)

Roberts, F. E., III

1995-01-01

This report presents a study on the effect of material processing parameters used in layer-by-layer material construction on the surface finish of a model to be used as an investment casting pattern. The data presented relate specifically to fused deposition modeling using a machinable wax.

Study of process parameter on mist lubrication of Titanium (Grade 5) alloy

NASA Astrophysics Data System (ADS)

Maity, Kalipada; Pradhan, Swastik

2017-02-01

This paper deals with the machinability of Ti-6Al-4V alloy with mist cooling lubrication using carbide inserts. The influence of process parameter on the cutting forces, evolution of tool wear, surface finish of the workpiece, material removal rate and chip reduction coefficient have been investigated. Weighted principal component analysis coupled with grey relational analysis optimization is applied to identify the optimum setting of the process parameter. Optimal condition of the process parameter was cutting speed at 160 m/min, feed at 0.16 mm/rev and depth of cut at 1.6 mm. Effects of cutting speed and depth of cut on the type of chips formation were observed. Most of the chips forms were long tubular and long helical type. Image analyses of the segmented chip were examined to study the shape and size of the saw tooth profile of serrated chips. It was found that by increasing cutting speed from 95 m/min to 160 m/min, the free surface lamella of the chips increased and the visibility of the saw tooth segment became clearer.

Effect of process parameters on microstructure and electrical conductivity during FSW of Al-6101 and Pure Copper

NASA Astrophysics Data System (ADS)

Sharma, Nidhi; Khan, Zahid A.; Siddiquee, Arshad Noor; Shihab, Suha K.; Atif Wahid, Mohd

2018-04-01

Copper (Cu) is predominantly used material as a conducting element in electrical and electronic components due to its high conductivity. Aluminum (Al) being lighter in weight and more conductive on weight basis than that of Cu is able to replace or partially replace Cu to make lighter and cost effective electrical components. Conventional methods of joining Al to Cu, such as, fusion welding process have many shortcomings. Friction Stir Welding (FSW) is a solid state welding process which overcomes the shortcoming of the fusion welding. FSW parameters affect the mechanical and electrical properties of the joint. This study aims to evaluate the effect of different process parameters such as shoulder diameter, pin offset, welding and rotational speed on the microstructure and electrical conductivity of the dissimilar Al-Cu joint. FSW is performed using cylindrical pin profile, and four process parameters. Each parameter at different levels is varied according to Taguchi’s L18 standard orthogonal array. It is found that the electrical conductivity of the FSWed joints are equal to that of aluminum at all the welded sections. FSW is found to be an effective technique to join Al to Cu without compromising with the electrical properties. However, the electrical conductivity gets influenced by the process parameters in the stir zone. The optimal combination of the FSW parameters for maximum electrical conductivity is determined. The analysis of variance (ANOVA) technique applied on stir zone suggests that the rotational speed and tool pin offset are the significant parameters to influence the electrical conductivity.

Theoretical study of hydrogen absorption-desorption on LaNi3.8Al1.2-xMnx using statistical physics treatment

NASA Astrophysics Data System (ADS)

Bouaziz, Nadia; Ben Manaa, Marwa; Ben Lamine, Abdelmottaleb

2017-11-01

The hydrogen absorption-desorption isotherms on LaNi3.8Al1.2-xMnx alloy at temperature T = 433 K is studied through various theoretical models. The analytical expressions of these models were deduced exploiting the grand canonical ensemble in statistical physics by taking some simplifying hypotheses. Among these models an adequate model which presents a good correlation with the experimental curves has been selected. The physicochemical parameters intervening in the absorption-desorption processes and involved in the model expressions could be directly deduced from the experimental isotherms by numerical simulation. Six parameters of the model are adjusted, namely the numbers of hydrogen atoms per site n1 and n2, the receptor site densities N1m and N2m, and the energetic parameters P1 and P2. The behaviors of these parameters are discussed in relation with absorption and desorption processes to better understand and compare these phenomena. Thanks to the energetic parameters, we calculated the sorption energies which are typically ranged between 266 and 269.4 KJ/mol for absorption process and between 267 and 269.5 KJ/mol for desorption process comparable to usual chemical bond energies. Using the adopted model expression, the thermodynamic potential functions which govern the absorption/desorption process such as internal energy Eint, free enthalpy of Gibbs G and entropy Sa are derived.

Study on Silicon Microstructure Processing Technology Based on Porous Silicon

NASA Astrophysics Data System (ADS)

Shang, Yingqi; Zhang, Linchao; Qi, Hong; Wu, Yalin; Zhang, Yan; Chen, Jing

2018-03-01

Aiming at the heterogeneity of micro - sealed cavity in silicon microstructure processing technology, the technique of preparing micro - sealed cavity of porous silicon is proposed. The effects of different solutions, different substrate doping concentrations, different current densities, and different etching times on the rate, porosity, thickness and morphology of the prepared porous silicon were studied. The porous silicon was prepared by different process parameters and the prepared porous silicon was tested and analyzed. For the test results, optimize the process parameters and experiments. The experimental results show that the porous silicon can be controlled by optimizing the parameters of the etching solution and the doping concentration of the substrate, and the preparation of porous silicon with different porosity can be realized by different doping concentration, so as to realize the preparation of silicon micro-sealed cavity, to solve the sensor sensitive micro-sealed cavity structure heterogeneous problem, greatly increasing the application of the sensor.

New generation photoelectric converter structure optimization using nano-structured materials

NASA Astrophysics Data System (ADS)

Dronov, A.; Gavrilin, I.; Zheleznyakova, A.

2014-12-01

In present work the influence of anodizing process parameters on PAOT geometric parameters for optimizing and increasing ETA-cell efficiency was studied. During the calculations optimal geometrical parameters were obtained. Parameters such as anodizing current density, electrolyte composition and temperature, as well as the anodic oxidation process time were selected for this investigation. Using the optimized TiO2 photoelectrode layer with 3,6 μm porous layer thickness and pore diameter more than 80 nm the ETA-cell efficiency has been increased by 3 times comparing to not nanostructured TiO2 photoelectrode.

Parameter-induced uncertainty quantification of a regional N2O and NO3 inventory using the biogeochemical model LandscapeDNDC

NASA Astrophysics Data System (ADS)

Haas, Edwin; Klatt, Steffen; Kraus, David; Werner, Christian; Ruiz, Ignacio Santa Barbara; Kiese, Ralf; Butterbach-Bahl, Klaus

2014-05-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional and national scales and are outlined as the most advanced methodology (Tier 3) for national emission inventory in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems like arable land and grasslands and are thus thought to be widely applicable at various spatial and temporal scales. The high complexity of ecosystem processes mirrored by such models requires a large number of model parameters. Many of those parameters are lumped parameters describing simultaneously the effect of environmental drivers on e.g. microbial community activity and individual processes. Thus, the precise quantification of true parameter states is often difficult or even impossible. As a result model uncertainty is not solely originating from input uncertainty but also subject to parameter-induced uncertainty. In this study we quantify regional parameter-induced model uncertainty on nitrous oxide (N2O) emissions and nitrate (NO3) leaching from arable soils of Saxony (Germany) using the biogeochemical model LandscapeDNDC. For this we calculate a regional inventory using a joint parameter distribution for key parameters describing microbial C and N turnover processes as obtained by a Bayesian calibration study. We representatively sampled 400 different parameter vectors from the discrete joint parameter distribution comprising approximately 400,000 parameter combinations and used these to calculate 400 individual realizations of the regional inventory. The spatial domain (represented by 4042 polygons) is set up with spatially explicit soil and climate information and a region-typical 3-year crop rotation consisting of winter wheat, rape- seed, and winter barley. Average N2O emission from arable soils in the state of Saxony across all 400 realizations was 1.43 ± 1.25 [kg N / ha] with a median value of 1.05 [kg N / ha]. Using the default IPCC emission factor approach (Tier 1) for direct emissions reveal a higher average N2O emission of 1.51 [kg N / ha] due to fertilizer use. In the regional uncertainty quantification the 20% likelihood range for N2O emissions is 0.79 - 1.37 [kg N / ha] (50% likelihood: 0.46 - 2.05 [kg N / ha]; 90% likelihood: 0.11 - 4.03 [kg N / ha]). Respective quantities were calculated for nitrate leaching. The method has proven its applicability to quantify parameter-induced uncertainty of simulated regional greenhouse gas emission and nitrate leaching inventories using process based biogeochemical models.

Experiments for practical education in process parameter optimization for selective laser sintering to increase workpiece quality

NASA Astrophysics Data System (ADS)

Reutterer, Bernd; Traxler, Lukas; Bayer, Natascha; Drauschke, Andreas

2016-04-01

Selective Laser Sintering (SLS) is considered as one of the most important additive manufacturing processes due to component stability and its broad range of usable materials. However the influence of the different process parameters on mechanical workpiece properties is still poorly studied, leading to the fact that further optimization is necessary to increase workpiece quality. In order to investigate the impact of various process parameters, laboratory experiments are implemented to improve the understanding of the SLS limitations and advantages on an educational level. Experiments are based on two different workstations, used to teach students the fundamentals of SLS. First of all a 50 W CO2 laser workstation is used to investigate the interaction of the laser beam with the used material in accordance with varied process parameters to analyze a single-layered test piece. Second of all the FORMIGA P110 laser sintering system from EOS is used to print different 3D test pieces in dependence on various process parameters. Finally quality attributes are tested including warpage, dimension accuracy or tensile strength. For dimension measurements and evaluation of the surface structure a telecentric lens in combination with a camera is used. A tensile test machine allows testing of the tensile strength and the interpreting of stress-strain curves. The developed laboratory experiments are suitable to teach students the influence of processing parameters. In this context they will be able to optimize the input parameters depending on the component which has to be manufactured and to increase the overall quality of the final workpiece.

A hyperbolastic type-I diffusion process: Parameter estimation by means of the firefly algorithm.

PubMed

Barrera, Antonio; Román-Román, Patricia; Torres-Ruiz, Francisco

2018-01-01

A stochastic diffusion process, whose mean function is a hyperbolastic curve of type I, is presented. The main characteristics of the process are studied and the problem of maximum likelihood estimation for the parameters of the process is considered. To this end, the firefly metaheuristic optimization algorithm is applied after bounding the parametric space by a stagewise procedure. Some examples based on simulated sample paths and real data illustrate this development. Copyright © 2017 Elsevier B.V. All rights reserved.

A case study: application of statistical process control tool for determining process capability and sigma level.

PubMed

Chopra, Vikram; Bairagi, Mukesh; Trivedi, P; Nagar, Mona

2012-01-01

Statistical process control is the application of statistical methods to the measurement and analysis of variation process. Various regulatory authorities such as Validation Guidance for Industry (2011), International Conference on Harmonisation ICH Q10 (2009), the Health Canada guidelines (2009), Health Science Authority, Singapore: Guidance for Product Quality Review (2008), and International Organization for Standardization ISO-9000:2005 provide regulatory support for the application of statistical process control for better process control and understanding. In this study risk assessments, normal probability distributions, control charts, and capability charts are employed for selection of critical quality attributes, determination of normal probability distribution, statistical stability, and capability of production processes, respectively. The objective of this study is to determine tablet production process quality in the form of sigma process capability. By interpreting data and graph trends, forecasting of critical quality attributes, sigma process capability, and stability of process were studied. The overall study contributes to an assessment of process at the sigma level with respect to out-of-specification attributes produced. Finally, the study will point to an area where the application of quality improvement and quality risk assessment principles for achievement of six sigma-capable processes is possible. Statistical process control is the most advantageous tool for determination of the quality of any production process. This tool is new for the pharmaceutical tablet production process. In the case of pharmaceutical tablet production processes, the quality control parameters act as quality assessment parameters. Application of risk assessment provides selection of critical quality attributes among quality control parameters. Sequential application of normality distributions, control charts, and capability analyses provides a valid statistical process control study on process. Interpretation of such a study provides information about stability, process variability, changing of trends, and quantification of process ability against defective production. Comparative evaluation of critical quality attributes by Pareto charts provides the least capable and most variable process that is liable for improvement. Statistical process control thus proves to be an important tool for six sigma-capable process development and continuous quality improvement.

Development of process parameters for 22 nm PMOS using 2-D analytical modeling

NASA Astrophysics Data System (ADS)

Maheran, A. H. Afifah; Menon, P. S.; Ahmad, I.; Shaari, S.; Faizah, Z. A. Noor

2015-04-01

The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (ILEAK) on PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO2) and tungsten silicide (WSix). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum ILEAK where the maximum predicted ILEAK value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device's leakage current. The absolute process parameters combination results in ILEAK mean value of 3.96821 nA/µm where is far lower than the predicted value.

Development of process parameters for 22 nm PMOS using 2-D analytical modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maheran, A. H. Afifah; Menon, P. S.; Shaari, S.

2015-04-24

The complementary metal-oxide-semiconductor field effect transistor (CMOSFET) has become major challenge to scaling and integration. Innovation in transistor structures and integration of novel materials are necessary to sustain this performance trend. CMOS variability in the scaling technology becoming very important concern due to limitation of process control; over statistically variability related to the fundamental discreteness and materials. Minimizing the transistor variation through technology optimization and ensuring robust product functionality and performance is the major issue.In this article, the continuation study on process parameters variations is extended and delivered thoroughly in order to achieve a minimum leakage current (I{sub LEAK}) onmore » PMOS planar transistor at 22 nm gate length. Several device parameters are varies significantly using Taguchi method to predict the optimum combination of process parameters fabrication. A combination of high permittivity material (high-k) and metal gate are utilized accordingly as gate structure where the materials include titanium dioxide (TiO{sub 2}) and tungsten silicide (WSi{sub x}). Then the L9 of the Taguchi Orthogonal array is used to analyze the device simulation where the results of signal-to-noise ratio (SNR) of Smaller-the-Better (STB) scheme are studied through the percentage influences of the process parameters. This is to achieve a minimum I{sub LEAK} where the maximum predicted I{sub LEAK} value by International Technology Roadmap for Semiconductors (ITRS) 2011 is said to should not above 100 nA/µm. Final results shows that the compensation implantation dose acts as the dominant factor with 68.49% contribution in lowering the device’s leakage current. The absolute process parameters combination results in I{sub LEAK} mean value of 3.96821 nA/µm where is far lower than the predicted value.« less

Multi-parameter comparison of a standardized mixed meal tolerance test in healthy and type 2 diabetic subjects: the PhenFlex challenge.

PubMed

Wopereis, Suzan; Stroeve, Johanna H M; Stafleu, Annette; Bakker, Gertruud C M; Burggraaf, Jacobus; van Erk, Marjan J; Pellis, Linette; Boessen, Ruud; Kardinaal, Alwine A F; van Ommen, Ben

2017-01-01

A key feature of metabolic health is the ability to adapt upon dietary perturbations. Recently, it was shown that metabolic challenge tests in combination with the new generation biomarkers allow the simultaneous quantification of major metabolic health processes. Currently, applied challenge tests are largely non-standardized. A systematic review defined an optimal nutritional challenge test, the "PhenFlex test" (PFT). This study aimed to prove that PFT modulates all relevant processes governing metabolic health thereby allowing to distinguish subjects with different metabolic health status. Therefore, 20 healthy and 20 type 2 diabetic (T2D) male subjects were challenged both by PFT and oral glucose tolerance test (OGTT). During the 8-h response time course, 132 parameters were quantified that report on 26 metabolic processes distributed over 7 organs (gut, liver, adipose, pancreas, vasculature, muscle, kidney) and systemic stress. In healthy subjects, 110 of the 132 parameters showed a time course response. Patients with T2D showed 18 parameters to be significantly different after overnight fasting compared to healthy subjects, while 58 parameters were different in the post-challenge time course after the PFT. This demonstrates the added value of PFT in distinguishing subjects with different health status. The OGTT and PFT response was highly comparable for glucose metabolism as identical amounts of glucose were present in both challenge tests. Yet the PFT reports on additional processes, including vasculature, systemic stress, and metabolic flexibility. The PFT enables the quantification of all relevant metabolic processes involved in maintaining or regaining homeostasis of metabolic health. Studying both healthy subjects and subjects with impaired metabolic health showed that the PFT revealed new processes laying underneath health. This study provides the first evidence towards adopting the PFT as gold standard in nutrition research.

Observing continuous change in heart rate variability and photoplethysmography-derived parameters during the process of pain production/relief with thermal stimuli.

PubMed

Ye, Jing-Jhao; Lee, Kuan-Ting; Lin, Jing-Siang; Chuang, Chiung-Cheng

2017-01-01

Continuously monitoring and efficiently managing pain has become an important issue. However, no study has investigated a change in physiological parameters during the process of pain production/relief. This study modeled the process of pain production/relief using ramped thermal stimulation (no pain: 37°C water, process of pain production: a heating rate of 1°C/min, and subject feels pain: water kept at the painful temperature for each subject, with each segment lasting 10 min). In this duration, the variation of the heat rate variability and photoplethysmography-derived parameters was observed. A total of 40 healthy individuals participated: 30 in the trial group (14 males and 16 females with a mean age of 22.5±1.9 years) and 10 in the control group (7 males and 3 females with a mean age of 22.5±1.3 years). The results showed that the numeric rating scale value was 5.03±1.99 when the subjects felt pain, with a temperature of 43.54±1.70°C. Heart rate, R-R interval, low frequency, high frequency, photoplethysmography amplitude, baseline, and autonomic nervous system state showed significant changes during the pain production process, but these changes differed during the period Segment D (painful temperature 10: min). In summary, the study observed that physiological parameters changed qualitatively during the process of pain production and relief and found that the high frequency, low frequency, and photoplethysmography parameters seemed to have different responses in four situations (no pain, pain production, pain experienced, and pain relief). The trends of these variations may be used as references in the clinical setting for continuously observing pain intensity.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

A holistic approach towards defined product attributes by Maillard-type food processing.

PubMed

Davidek, Tomas; Illmann, Silke; Rytz, Andreas; Blank, Imre

2013-07-01

A fractional factorial experimental design was used to quantify the impact of process and recipe parameters on selected product attributes of extruded products (colour, viscosity, acrylamide, and the flavour marker 4-hydroxy-2,5-dimethyl-3(2H)-furanone, HDMF). The study has shown that recipe parameters (lysine, phosphate) can be used to modulate the HDMF level without changing the specific mechanical energy (SME) and consequently the texture of the product, while processing parameters (temperature, moisture) impact both HDMF and SME in parallel. Similarly, several parameters, including phosphate level, temperature and moisture, simultaneously impact both HDMF and acrylamide formation, while pH and addition of lysine showed different trends. Therefore, the latter two options can be used to mitigate acrylamide without a negative impact on flavour. Such a holistic approach has been shown as a powerful tool to optimize various product attributes upon food processing.

Kinetics modelling of color deterioration during thermal processing of tomato paste with the use of response surface methodology

NASA Astrophysics Data System (ADS)

Ganje, Mohammad; Jafari, Seid Mahdi; Farzaneh, Vahid; Malekjani, Narges

2018-06-01

To study the kinetics of color degradation, the tomato paste was designed to be processed at three different temperatures including 60, 70 and 80 °C for 25, 50, 75 and 100 min. a/b ratio, total color difference, saturation index and hue angle were calculated with the use of three main color parameters including L (lightness), a (redness-greenness) and b (yellowness-blueness) values. Kinetics of color degradation was developed by Arrhenius equation and the alterations were modelled with the use of response surface methodology (RSM). It was detected that all of the studied responses followed a first order reaction kinetics with an exception in TCD parameter (zeroth order). TCD and a/b respectively with the highest and lowest activation energy presented the highest sensitivity to the temperature alterations. The maximum and minimum rates of alterations were observed by TCD and b parameters, respectively. It was obviously determined that all of the studied parameters (responses) were affected by the selected independent parameters.

Comparative Analyses of Creep Models of a Solid Propellant

NASA Astrophysics Data System (ADS)

Zhang, J. B.; Lu, B. J.; Gong, S. F.; Zhao, S. P.

2018-05-01

The creep experiments of a solid propellant samples under five different stresses are carried out at 293.15 K and 323.15 K. In order to express the creep properties of this solid propellant, the viscoelastic model i.e. three Parameters solid, three Parameters fluid, four Parameters solid, four Parameters fluid and exponential model are involved. On the basis of the principle of least squares fitting, and different stress of all the parameters for the models, the nonlinear fitting procedure can be used to analyze the creep properties. The study shows that the four Parameters solid model can best express the behavior of creep properties of the propellant samples. However, the three Parameters solid and exponential model cannot very well reflect the initial value of the creep process, while the modified four Parameters models are found to agree well with the acceleration characteristics of the creep process.

The combined effect of wet granulation process parameters and dried granule moisture content on tablet quality attributes.

PubMed

Gabbott, Ian P; Al Husban, Farhan; Reynolds, Gavin K

2016-09-01

A pharmaceutical compound was used to study the effect of batch wet granulation process parameters in combination with the residual moisture content remaining after drying on granule and tablet quality attributes. The effect of three batch wet granulation process parameters was evaluated using a multivariate experimental design, with a novel constrained design space. Batches were characterised for moisture content, granule density, crushing strength, porosity, disintegration time and dissolution. Mechanisms of the effect of the process parameters on the granule and tablet quality attributes are proposed. Water quantity added during granulation showed a significant effect on granule density and tablet dissolution rate. Mixing time showed a significant effect on tablet crushing strength, and mixing speed showed a significant effect on the distribution of tablet crushing strengths obtained. The residual moisture content remaining after granule drying showed a significant effect on tablet crushing strength. The effect of moisture on tablet tensile strength has been reported before, but not in combination with granulation parameters and granule properties, and the impact on tablet dissolution was not assessed. Correlations between the energy input during granulation, the density of granules produced, and the quality attributes of the final tablets were also identified. Understanding the impact of the granulation and drying process parameters on granule and tablet properties provides a basis for process optimisation and scaling. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimisation on processing parameters for minimising warpage on side arm using response surface methodology (RSM) and particle swarm optimisation (PSO)

NASA Astrophysics Data System (ADS)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Sazli, M.; Yahya, Z. R.

2017-09-01

This study presents the application of optimisation method to reduce the warpage of side arm part. Autodesk Moldflow Insight software was integrated into this study to analyse the warpage. The design of Experiment (DOE) for Response Surface Methodology (RSM) was constructed and by using the equation from RSM, Particle Swarm Optimisation (PSO) was applied. The optimisation method will result in optimised processing parameters with minimum warpage. Mould temperature, melt temperature, packing pressure, packing time and cooling time was selected as the variable parameters. Parameters selection was based on most significant factor affecting warpage stated by previous researchers. The results show that warpage was improved by 28.16% for RSM and 28.17% for PSO. The warpage improvement in PSO from RSM is only by 0.01 %. Thus, the optimisation using RSM is already efficient to give the best combination parameters and optimum warpage value for side arm part. The most significant parameters affecting warpage are packing pressure.

Study of Material Consolidation at Higher Throughput Parameters in Selective Laser Melting of Inconel 718

NASA Technical Reports Server (NTRS)

Prater, Tracie

2016-01-01

Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. SLM stands poised to revolutionize propulsion manufacturing, but there are a number of technical questions that must be addressed in order to achieve rapid, efficient fabrication and ensure adequate performance of parts manufactured using this process in safety-critical flight applications. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this work is to characterize the impact of higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. In phase I of this work, density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, hatch spacing, and layer thickness) and material consolidation (assessed in terms of as-built density and porosity). Phase II additionally considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the same higher energy parameter regime considered in the phase I work. Density and microstructure represent the "first-gate" metrics for determining the adequacy of the SLM process in this parameter range and, as a critical initial indicator of material quality, will factor into a follow-on DOE that assesses the impact of these parameters on mechanical properties. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

Isotherm Modelling, Kinetic Study and Optimization of Batch Parameters Using Response Surface Methodology for Effective Removal of Cr(VI) Using Fungal Biomass

PubMed Central

Chidambaram, Ramalingam

2015-01-01

Biosorption is a promising alternative method to replace the existing conventional technique for Cr(VI) removal from the industrial effluent. In the present experimental design, the removal of Cr(VI) from the aqueous solution was studied by Aspergillus niger MSR4 under different environmental conditions in the batch systems. The optimum conditions of biosorption were determined by investigating pH (2.0) and temperature (27°C). The effects of parameters such as biomass dosage (g/L), initial Cr(VI) concentration (mg/L) and contact time (min) on Cr(VI) biosorption were analyzed using a three parameter Box–Behnken design (BBD). The experimental data well fitted to the Langmuir isotherm, in comparison to the other isotherm models tested. The results of the D-R isotherm model suggested that a chemical ion-exchange mechanism was involved in the biosorption process. The biosorption process followed the pseudo-second-order kinetic model, which indicates that the rate limiting step is chemisorption process. Fourier transform infrared (FT-IR) spectroscopic studies revealed the possible involvement of functional groups, such as hydroxyl, carboxyl, amino and carbonyl group in the biosorption process. The thermodynamic parameters for Cr(VI) biosorption were also calculated, and the negative ∆Gº values indicated the spontaneous nature of biosorption process. PMID:25786227

Warpage minimization on wheel caster by optimizing process parameters using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, it is important to keep the productivity increase constantly with least of waste produced such as warpage defect. Thus, this study is concerning on minimizing warpage defect on wheel caster part. Apart from eliminating product wastes, this project also giving out best optimization techniques using response surface methodology. This research studied on five parameters A-packing pressure, B-packing time, C-mold temperature, D-melting temperature and E-cooling time. The optimization showed that packing pressure is the most significant parameter. Warpage have been improved 42.64% from 0.6524 mm to 0.3742mm.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

Solution blow spinning: parameters optimization and effects on the properties of nanofibers from poly(lactic) acid/dimethyl carbonate solutions

USDA-ARS?s Scientific Manuscript database

Solution blow spinning (SBS) is a process to produce non-woven fiber sheets with high porosity and an extremely large amount of surface area. In this study, a Box-Behnken experimental design (BBD) was used to optimize the processing parameters for the production of nanofibers from polymer solutions ...

Uncertainty estimation of the self-thinning process by Maximum-Entropy Principle

Treesearch

Shoufan Fang; George Z. Gertner

2000-01-01

When available information is scarce, the Maximum-Entropy Principle can estimate the distributions of parameters. In our case study, we estimated the distributions of the parameters of the forest self-thinning process based on literature information, and we derived the conditional distribution functions and estimated the 95 percent confidence interval (CI) of the self-...

Optimization of process parameters for RF sputter deposition of tin-nitride thin-films

NASA Astrophysics Data System (ADS)

Jangid, Teena; Rao, G. Mohan

2018-05-01

Radio frequency Magnetron sputtering technique was employed to deposit Tin-nitride thin films on Si and glass substrate at different process parameters. Influence of varying parameters like substrate temperature, target-substrate distance and RF power is studied in detail. X-ray diffraction method is used as a key technique for analyzing the changes in the stoichiometric and structural properties of the deposited films. Depending on the combination of deposition parameters, crystalline as well as amorphous films were obtained. Pure tin-nitride thin films were deposited at 15W RF power and 600°C substrate temperature with target-substrate distance fixed at 10cm. Bandgap value of 1.6 eV calculated for the film deposited at optimum process conditions matches well with reported values.

Optimization of Vacuum Impregnation with Calcium Lactate of Minimally Processed Melon and Shelf-Life Study in Real Storage Conditions.

PubMed

Tappi, Silvia; Tylewicz, Urszula; Romani, Santina; Siroli, Lorenzo; Patrignani, Francesca; Dalla Rosa, Marco; Rocculi, Pietro

2016-10-05

Vacuum impregnation (VI) is a processing operation that permits the impregnation of fruit and vegetable porous tissues with a fast and more homogeneous penetration of active compounds compared to the classical diffusion processes. The objective of this research was to investigate the impact on VI treatment with the addition of calcium lactate on qualitative parameters of minimally processed melon during storage. For this aim, this work was divided in 2 parts. Initially, the optimization of process parameters was carried out in order to choose the optimal VI conditions for improving texture characteristics of minimally processed melon that were then used to impregnate melons for a shelf-life study in real storage conditions. On the basis of a 2 3 factorial design, the effect of Calcium lactate (CaLac) concentration between 0% and 5% and of minimum pressure (P) between 20 and 60 MPa were evaluated on color and texture. Processing parameters corresponding to 5% CaLac concentration and 60 MPa of minimum pressure were chosen for the storage study, during which the modifications of main qualitative parameters were evaluated. Despite of the high variability of the raw material, results showed that VI allowed a better maintenance of texture during storage. Nevertheless, other quality traits were negatively affected by the application of vacuum. Impregnated products showed a darker and more translucent appearance on the account of the alteration of the structural properties. Moreover microbial shelf-life was reduced to 4 d compared to the 7 obtained for control and dipped samples. © 2016 Institute of Food Technologists®.

A Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies

PubMed Central

Jobard, Elodie; Trédan, Olivier; Postoly, Déborah; André, Fabrice; Martin, Anne-Laure; Elena-Herrmann, Bénédicte; Boyault, Sandrine

2016-01-01

The recent thriving development of biobanks and associated high-throughput phenotyping studies requires the elaboration of large-scale approaches for monitoring biological sample quality and compliance with standard protocols. We present a metabolomic investigation of human blood samples that delineates pitfalls and guidelines for the collection, storage and handling procedures for serum and plasma. A series of eight pre-processing technical parameters is systematically investigated along variable ranges commonly encountered across clinical studies. While metabolic fingerprints, as assessed by nuclear magnetic resonance, are not significantly affected by altered centrifugation parameters or delays between sample pre-processing (blood centrifugation) and storage, our metabolomic investigation highlights that both the delay and storage temperature between blood draw and centrifugation are the primary parameters impacting serum and plasma metabolic profiles. Storing the blood drawn at 4 °C is shown to be a reliable routine to confine variability associated with idle time prior to sample pre-processing. Based on their fine sensitivity to pre-analytical parameters and protocol variations, metabolic fingerprints could be exploited as valuable ways to determine compliance with standard procedures and quality assessment of blood samples within large multi-omic clinical and translational cohort studies. PMID:27929400

Evaluating Acoustic Emission Signals as an in situ process monitoring technique for Selective Laser Melting (SLM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisher, Karl A.; Candy, Jim V.; Guss, Gabe

2016-10-14

In situ real-time monitoring of the Selective Laser Melting (SLM) process has significant implications for the AM community. The ability to adjust the SLM process parameters during a build (in real-time) can save time, money and eliminate expensive material waste. Having a feedback loop in the process would allow the system to potentially ‘fix’ problem regions before a next powder layer is added. In this study we have investigated acoustic emission (AE) phenomena generated during the SLM process, and evaluated the results in terms of a single process parameter, of an in situ process monitoring technique.

The Influence of Friction Stir Weld Tool Form and Welding Parameters on Weld Structure and Properties: Nugget Bulge in Self-Reacting Friction Stir Welds

NASA Technical Reports Server (NTRS)

Schneider, Judy; Nunes, Arthur C., Jr.; Brendel, Michael S.

2010-01-01

Although friction stir welding (FSW) was patented in 1991, process development has been based upon trial and error and the literature still exhibits little understanding of the mechanisms determining weld structure and properties. New concepts emerging from a better understanding of these mechanisms enhance the ability of FSW engineers to think about the FSW process in new ways, inevitably leading to advances in the technology. A kinematic approach in which the FSW flow process is decomposed into several simple flow components has been found to explain the basic structural features of FSW welds and to relate them to tool geometry and process parameters. Using this modelling approach, this study reports on a correlation between the features of the weld nugget, process parameters, weld tool geometry, and weld strength. This correlation presents a way to select process parameters for a given tool geometry so as to optimize weld strength. It also provides clues that may ultimately explain why the weld strength varies within the sample population.

A Four-parameter Budyko Equation for Mean Annual Water Balance

NASA Astrophysics Data System (ADS)

Tang, Y.; Wang, D.

2016-12-01

In this study, a four-parameter Budyko equation for long-term water balance at watershed scale is derived based on the proportionality relationships of the two-stage partitioning of precipitation. The four-parameter Budyko equation provides a practical solution to balance model simplicity and representation of dominated hydrologic processes. Under the four-parameter Budyko framework, the key hydrologic processes related to the lower bound of Budyko curve are determined, that is, the lower bound is corresponding to the situation when surface runoff and initial evaporation not competing with base flow generation are zero. The derived model is applied to 166 MOPEX watersheds in United States, and the dominant controlling factors on each parameter are determined. Then, four statistical models are proposed to predict the four model parameters based on the dominant controlling factors, e.g., saturated hydraulic conductivity, fraction of sand, time period between two storms, watershed slope, and Normalized Difference Vegetation Index. This study shows a potential application of the four-parameter Budyko equation to constrain land-surface parameterizations in ungauged watersheds or general circulation models.

Application of quality by design principles to the development and technology transfer of a major process improvement for the manufacture of a recombinant protein.

PubMed

Looby, Mairead; Ibarra, Neysi; Pierce, James J; Buckley, Kevin; O'Donovan, Eimear; Heenan, Mary; Moran, Enda; Farid, Suzanne S; Baganz, Frank

2011-01-01

This study describes the application of quality by design (QbD) principles to the development and implementation of a major manufacturing process improvement for a commercially distributed therapeutic protein produced in Chinese hamster ovary cell culture. The intent of this article is to focus on QbD concepts, and provide guidance and understanding on how the various components combine together to deliver a robust process in keeping with the principles of QbD. A fed-batch production culture and a virus inactivation step are described as representative examples of upstream and downstream unit operations that were characterized. A systematic approach incorporating QbD principles was applied to both unit operations, involving risk assessment of potential process failure points, small-scale model qualification, design and execution of experiments, definition of operating parameter ranges and process validation acceptance criteria followed by manufacturing-scale implementation and process validation. Statistical experimental designs were applied to the execution of process characterization studies evaluating the impact of operating parameters on product quality attributes and process performance parameters. Data from process characterization experiments were used to define the proven acceptable range and classification of operating parameters for each unit operation. Analysis of variance and Monte Carlo simulation methods were used to assess the appropriateness of process design spaces. Successful implementation and validation of the process in the manufacturing facility and the subsequent manufacture of hundreds of batches of this therapeutic protein verifies the approaches taken as a suitable model for the development, scale-up and operation of any biopharmaceutical manufacturing process. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

Determination of thermodynamic and transport parameters of naphthenic acids and organic process chemicals in oil sand tailings pond water.

PubMed

Wang, Xiaomeng; Robinson, Lisa; Wen, Qing; Kasperski, Kim L

2013-07-01

Oil sand tailings pond water contains naphthenic acids and process chemicals (e.g., alkyl sulphates, quaternary ammonium compounds, and alkylphenol ethoxylates). These chemicals are toxic and can seep through the foundation of the tailings pond to the subsurface, potentially affecting the quality of groundwater. As a result, it is important to measure the thermodynamic and transport parameters of these chemicals in order to study the transport behavior of contaminants through the foundation as well as underground. In this study, batch adsorption studies and column experiments were performed. It was found that the transport parameters of these chemicals are related to their molecular structures and other properties. The computer program (CXTFIT) was used to further evaluate the transport process in the column experiments. The results from this study show that the transport of naphthenic acids in a glass column is an equilibrium process while the transport of process chemicals seems to be a non-equilibrium process. At the end of this paper we present a real-world case study in which the transport of the contaminants through the foundation of an external tailings pond is calculated using the lab-measured data. The results show that long-term groundwater monitoring of contaminant transport at the oil sand mining site may be necessary to avoid chemicals from reaching any nearby receptors.

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

Investigation about the Chrome Steel Wire Arc Spray Process and the Resulting Coating Properties

NASA Astrophysics Data System (ADS)

Wilden, J.; Bergmann, J. P.; Jahn, S.; Knapp, S.; van Rodijnen, F.; Fischer, G.

2007-12-01

Nowadays, wire-arc spraying of chromium steel has gained an important market share for corrosion and wear protection applications. However, detailed studies are the basis for further process optimization. In order to optimize the process parameters and to evaluate the effects of the spray parameters DoE-based experiments had been carried out with high-speed camera shoots. In this article, the effects of spray current, voltage, and atomizing gas pressure on the particle jet properties, mean particle velocity and mean particle temperature and plume width on X46Cr13 wire are presented using an online process monitoring device. Moreover, the properties of the coatings concerning the morphology, composition and phase formation were subject of the investigations using SEM, EDX, and XRD-analysis. These deep investigations allow a defined verification of the influence of process parameters on spray plume and coating properties and are the basis for further process optimization.

Prediction of Tensile Strength of Friction Stir Weld Joints with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network

NASA Technical Reports Server (NTRS)

Dewan, Mohammad W.; Huggett, Daniel J.; Liao, T. Warren; Wahab, Muhammad A.; Okeil, Ayman M.

2015-01-01

Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed (??), plunge force (????), and welding speed (??) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables (??,??,????,??????) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

UHF Signal Processing and Pattern Recognition of Partial Discharge in Gas-Insulated Switchgear Using Chromatic Methodology

PubMed Central

Wang, Xiaohua; Li, Xi; Rong, Mingzhe; Xie, Dingli; Ding, Dan; Wang, Zhixiang

2017-01-01

The ultra-high frequency (UHF) method is widely used in insulation condition assessment. However, UHF signal processing algorithms are complicated and the size of the result is large, which hinders extracting features and recognizing partial discharge (PD) patterns. This article investigated the chromatic methodology that is novel in PD detection. The principle of chromatic methodologies in color science are introduced. The chromatic processing represents UHF signals sparsely. The UHF signals obtained from PD experiments were processed using chromatic methodology and characterized by three parameters in chromatic space (H, L, and S representing dominant wavelength, signal strength, and saturation, respectively). The features of the UHF signals were studied hierarchically. The results showed that the chromatic parameters were consistent with conventional frequency domain parameters. The global chromatic parameters can be used to distinguish UHF signals acquired by different sensors, and they reveal the propagation properties of the UHF signal in the L-shaped gas-insulated switchgear (GIS). Finally, typical PD defect patterns had been recognized by using novel chromatic parameters in an actual GIS tank and good performance of recognition was achieved. PMID:28106806

UHF Signal Processing and Pattern Recognition of Partial Discharge in Gas-Insulated Switchgear Using Chromatic Methodology.

PubMed

Wang, Xiaohua; Li, Xi; Rong, Mingzhe; Xie, Dingli; Ding, Dan; Wang, Zhixiang

2017-01-18

The ultra-high frequency (UHF) method is widely used in insulation condition assessment. However, UHF signal processing algorithms are complicated and the size of the result is large, which hinders extracting features and recognizing partial discharge (PD) patterns. This article investigated the chromatic methodology that is novel in PD detection. The principle of chromatic methodologies in color science are introduced. The chromatic processing represents UHF signals sparsely. The UHF signals obtained from PD experiments were processed using chromatic methodology and characterized by three parameters in chromatic space ( H , L , and S representing dominant wavelength, signal strength, and saturation, respectively). The features of the UHF signals were studied hierarchically. The results showed that the chromatic parameters were consistent with conventional frequency domain parameters. The global chromatic parameters can be used to distinguish UHF signals acquired by different sensors, and they reveal the propagation properties of the UHF signal in the L-shaped gas-insulated switchgear (GIS). Finally, typical PD defect patterns had been recognized by using novel chromatic parameters in an actual GIS tank and good performance of recognition was achieved.

Single droplet drying step characterization in microsphere preparation.

PubMed

Al Zaitone, Belal; Lamprecht, Alf

2013-05-01

Spray drying processes are difficult to characterize since process parameters are not directly accessible. Acoustic levitation was used to investigate microencapsulation by spray drying on one single droplet facilitating the analyses of droplet behavior upon drying. Process parameters were simulated on a poly(lactide-co-glycolide)/ethyl acetate combination for microencapsulation. The results allowed quantifying the influence of process parameters such as temperature (0-40°C), polymer concentration (5-400 mg/ml), and droplet size (0.5-1.37 μl) on the drying time and drying kinetics as well as the particle morphology. The drying of polymer solutions at temperature of 21°C and concentration of 5 mg/ml, shows that the dimensionless particle diameter (Dp/D0) approaches 0.25 and the particle needs 350 s to dry. At 400 mg/ml, Dp/D0=0.8 and the drying time increases to one order of magnitude and a hollow particle is formed. The study demonstrates the benefit of using the acoustic levitator as a lab scale method to characterize and study the microparticle formation. This method can be considered as a helpful tool to mimic the full scale spray drying process by providing identical operational parameters such as air velocity, temperature, and variable droplet sizes. Copyright © 2013 Elsevier B.V. All rights reserved.

Study of gas production from shale reservoirs with multi-stage hydraulic fracturing horizontal well considering multiple transport mechanisms.

PubMed

Guo, Chaohua; Wei, Mingzhen; Liu, Hong

2018-01-01

Development of unconventional shale gas reservoirs (SGRs) has been boosted by the advancements in two key technologies: horizontal drilling and multi-stage hydraulic fracturing. A large number of multi-stage fractured horizontal wells (MsFHW) have been drilled to enhance reservoir production performance. Gas flow in SGRs is a multi-mechanism process, including: desorption, diffusion, and non-Darcy flow. The productivity of the SGRs with MsFHW is influenced by both reservoir conditions and hydraulic fracture properties. However, rare simulation work has been conducted for multi-stage hydraulic fractured SGRs. Most of them use well testing methods, which have too many unrealistic simplifications and assumptions. Also, no systematical work has been conducted considering all reasonable transport mechanisms. And there are very few works on sensitivity studies of uncertain parameters using real parameter ranges. Hence, a detailed and systematic study of reservoir simulation with MsFHW is still necessary. In this paper, a dual porosity model was constructed to estimate the effect of parameters on shale gas production with MsFHW. The simulation model was verified with the available field data from the Barnett Shale. The following mechanisms have been considered in this model: viscous flow, slip flow, Knudsen diffusion, and gas desorption. Langmuir isotherm was used to simulate the gas desorption process. Sensitivity analysis on SGRs' production performance with MsFHW has been conducted. Parameters influencing shale gas production were classified into two categories: reservoir parameters including matrix permeability, matrix porosity; and hydraulic fracture parameters including hydraulic fracture spacing, and fracture half-length. Typical ranges of matrix parameters have been reviewed. Sensitivity analysis have been conducted to analyze the effect of the above factors on the production performance of SGRs. Through comparison, it can be found that hydraulic fracture parameters are more sensitive compared with reservoir parameters. And reservoirs parameters mainly affect the later production period. However, the hydraulic fracture parameters have a significant effect on gas production from the early period. The results of this study can be used to improve the efficiency of history matching process. Also, it can contribute to the design and optimization of hydraulic fracture treatment design in unconventional SGRs.

Study of gas production from shale reservoirs with multi-stage hydraulic fracturing horizontal well considering multiple transport mechanisms

PubMed Central

Wei, Mingzhen; Liu, Hong

2018-01-01

Development of unconventional shale gas reservoirs (SGRs) has been boosted by the advancements in two key technologies: horizontal drilling and multi-stage hydraulic fracturing. A large number of multi-stage fractured horizontal wells (MsFHW) have been drilled to enhance reservoir production performance. Gas flow in SGRs is a multi-mechanism process, including: desorption, diffusion, and non-Darcy flow. The productivity of the SGRs with MsFHW is influenced by both reservoir conditions and hydraulic fracture properties. However, rare simulation work has been conducted for multi-stage hydraulic fractured SGRs. Most of them use well testing methods, which have too many unrealistic simplifications and assumptions. Also, no systematical work has been conducted considering all reasonable transport mechanisms. And there are very few works on sensitivity studies of uncertain parameters using real parameter ranges. Hence, a detailed and systematic study of reservoir simulation with MsFHW is still necessary. In this paper, a dual porosity model was constructed to estimate the effect of parameters on shale gas production with MsFHW. The simulation model was verified with the available field data from the Barnett Shale. The following mechanisms have been considered in this model: viscous flow, slip flow, Knudsen diffusion, and gas desorption. Langmuir isotherm was used to simulate the gas desorption process. Sensitivity analysis on SGRs’ production performance with MsFHW has been conducted. Parameters influencing shale gas production were classified into two categories: reservoir parameters including matrix permeability, matrix porosity; and hydraulic fracture parameters including hydraulic fracture spacing, and fracture half-length. Typical ranges of matrix parameters have been reviewed. Sensitivity analysis have been conducted to analyze the effect of the above factors on the production performance of SGRs. Through comparison, it can be found that hydraulic fracture parameters are more sensitive compared with reservoir parameters. And reservoirs parameters mainly affect the later production period. However, the hydraulic fracture parameters have a significant effect on gas production from the early period. The results of this study can be used to improve the efficiency of history matching process. Also, it can contribute to the design and optimization of hydraulic fracture treatment design in unconventional SGRs. PMID:29320489

Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Poissant, Dominique; Brissette, François

2015-11-01

This paper evaluated the effects of parametric reduction of a hydrological model on five regionalization methods and 267 catchments in the province of Quebec, Canada. The Sobol' variance-based sensitivity analysis was used to rank the model parameters by their influence on the model results and sequential parameter fixing was performed. The reduction in parameter correlations improved parameter identifiability, however this improvement was found to be minimal and was not transposed in the regionalization mode. It was shown that 11 of the HSAMI models' 23 parameters could be fixed with little or no loss in regionalization skill. The main conclusions were that (1) the conceptual lumped models used in this study did not represent physical processes sufficiently well to warrant parameter reduction for physics-based regionalization methods for the Canadian basins examined and (2) catchment descriptors did not adequately represent the relevant hydrological processes, namely snow accumulation and melt.

Estimation of Graded Response Model Parameters Using MULTILOG.

ERIC Educational Resources Information Center

Baker, Frank B.

1997-01-01

Describes an idiosyncracy of the MULTILOG (D. Thissen, 1991) parameter estimation process discovered during a simulation study involving the graded response model. A misordering reflected in boundary function location parameter estimates resulted in a large negative contribution to the true score followed by a large positive contribution. These…

Process parameters in the manufacture of ceramic ZnO nanofibers made by electrospinning

NASA Astrophysics Data System (ADS)

Nonato, Renato C.; Morales, Ana R.; Rocha, Mateus C.; Nista, Silvia V. G.; Mei, Lucia H. I.; Bonse, Baltus C.

2017-01-01

Zinc oxide (ZnO) nanofibers were prepared by electrospinning under different conditions using a solution of poly(vinyl alcohol) and zinc acetate as precursor. A 23 factorial design was made to study the influence of the process parameters in the electrospinning (collector distance, flow rate and voltage), and a 22 factorial design was made to study the influence of the calcination process (time and temperature). SEM images were made to analyze the fiber morphology before and after calcination process, and the images were made to measure the nanofiber diameter. X-ray diffraction was made to analyze the total precursor conversion to ZnO and the elimination of the polymeric carrier.

A combinaison of UV curing technology with ATL process

NASA Astrophysics Data System (ADS)

Balbzioui, I.; Hasiaoui, B.; Barbier, G.; L'hostis, G.; Laurent, F.; Ibrahim, A.; Durand, B.

2017-10-01

In order to reduce the time and the cost of manufacturing composite, UV curing technology combined with automated tape placement process (ATL) based on reverse approach by working with a fixed head was studied in this article. First, a brief description of the developed head placement is presented. Mechanical properties are then evaluated by varying process parameters, including compaction force and tape placement speed. Finally, a parametric study is carried out to identify suitable materials and process parameters to manufacture a photo composite material with high mechanical performances. The obtained results show that UV curing is a very good alternative for thermal polymerization because of its fast cure speed due to less dependency on temperature.

Process parameter dependent growth phenomena of naproxen nanosuspension manufactured by wet media milling.

PubMed

Bitterlich, A; Laabs, C; Krautstrunk, I; Dengler, M; Juhnke, M; Grandeury, A; Bunjes, H; Kwade, A

2015-05-01

The production of nanosuspensions has proved to be an effective method for overcoming bioavailability challenges of poorly water soluble drugs. Wet milling in stirred media mills and planetary ball mills has become an established top-down-method for producing such drug nanosuspensions. The quality of the resulting nanosuspension is determined by the stability against agglomeration on the one hand, and the process parameters of the mill on the other hand. In order to understand the occurring dependencies, a detailed screening study, not only on adequate stabilizers, but also on their optimum concentration was carried out for the active pharmaceutical ingredient (API) naproxen in a planetary ball mill. The type and concentration of the stabilizer had a pronounced influence on the minimum particle size obtained. With the best formulation the influence of the relevant process parameters on product quality was investigated to determine the grinding limit of naproxen. Besides the well known phenomenon of particle agglomeration, actual naproxen crystal growth and morphology alterations occurred during the process which has not been observed before. It was shown that, by adjusting the process parameters, those effects could be reduced or eliminated. Thus, besides real grinding and agglomeration a process parameter dependent ripening of the naproxen particles was identified to be a concurrent effect during the naproxen fine grinding process. Copyright © 2015 Elsevier B.V. All rights reserved.

Scaling and scale invariance of conservation laws in Reynolds transport theorem framework

NASA Astrophysics Data System (ADS)

Haltas, Ismail; Ulusoy, Suleyman

2015-07-01

Scale invariance is the case where the solution of a physical process at a specified time-space scale can be linearly related to the solution of the processes at another time-space scale. Recent studies investigated the scale invariance conditions of hydrodynamic processes by applying the one-parameter Lie scaling transformations to the governing equations of the processes. Scale invariance of a physical process is usually achieved under certain conditions on the scaling ratios of the variables and parameters involved in the process. The foundational axioms of hydrodynamics are the conservation laws, namely, conservation of mass, conservation of linear momentum, and conservation of energy from continuum mechanics. They are formulated using the Reynolds transport theorem. Conventionally, Reynolds transport theorem formulates the conservation equations in integral form. Yet, differential form of the conservation equations can also be derived for an infinitesimal control volume. In the formulation of the governing equation of a process, one or more than one of the conservation laws and, some times, a constitutive relation are combined together. Differential forms of the conservation equations are used in the governing partial differential equation of the processes. Therefore, differential conservation equations constitute the fundamentals of the governing equations of the hydrodynamic processes. Applying the one-parameter Lie scaling transformation to the conservation laws in the Reynolds transport theorem framework instead of applying to the governing partial differential equations may lead to more fundamental conclusions on the scaling and scale invariance of the hydrodynamic processes. This study will investigate the scaling behavior and scale invariance conditions of the hydrodynamic processes by applying the one-parameter Lie scaling transformation to the conservation laws in the Reynolds transport theorem framework.

Electrospraying of polymer solutions: Study of formulation and process parameters.

PubMed

Smeets, Annelies; Clasen, Christian; Van den Mooter, Guy

2017-10-01

Over the past decade, electrospraying has proven to be a promising method for the preparation of amorphous solid dispersions, an established formulation strategy to improve the oral bioavailability of poorly soluble drug compounds. Due to the lack of fundamental knowledge concerning adequate single nozzle electrospraying conditions, a trial-and-error approach is currently the only option. The objective of this paper is to study/investigate the influence of the different formulation and process parameters, as well as their interplay, on the formation of a stable cone-jet mode as a prerequisite for a reproducible production of monodisperse micro- and nanoparticles. To this purpose, different polymers commonly used in the formulation of solid dispersions were electrosprayed to map out the workable parameter ranges of the process. The experiments evaluate the importance of the experimental parameters as flow rate, electric potential difference and the distance between the tip of the nozzle and collector. Based on this, the type of solvent and the concentration of the polymer solutions, along with their viscosity and conductivity, were identified as determinative formulation parameters. This information is of utmost importance to rationally design further electrospraying methods for the preparation of amorphous solid dispersions. Copyright © 2017 Elsevier B.V. All rights reserved.

Toolpath Strategy and Optimum Combination of Machining Parameter during Pocket Mill Process of Plastic Mold Steels Material

NASA Astrophysics Data System (ADS)

Wibowo, Y. T.; Baskoro, S. Y.; Manurung, V. A. T.

2018-02-01

Plastic based products spread all over the world in many aspects of life. The ability to substitute other materials is getting stronger and wider. The use of plastic materials increases and become unavoidable. Plastic based mass production requires injection process as well Mold. The milling process of plastic mold steel material was done using HSS End Mill cutting tool that is widely used in a small and medium enterprise for the reason of its ability to be re sharpened and relatively inexpensive. Study on the effect of the geometry tool states that it has an important effect on the quality improvement. Cutting speed, feed rate, depth of cut and radii are input parameters beside to the tool path strategy. This paper aims to investigate input parameter and cutting tools behaviors within some different tool path strategy. For the reason of experiments efficiency Taguchi method and ANOVA were used. Response studied is surface roughness and cutting behaviors. By achieving the expected quality, no more additional process is required. Finally, the optimal combination of machining parameters will deliver the expected roughness and of course totally reduced cutting time. However actually, SMEs do not optimally use this data for cost reduction.

A Fundamental Study of Laser Beam Welding Aluminum-Lithium Alloy 2195 for Cryogenic Tank Applications

NASA Technical Reports Server (NTRS)

Martukanitz, R. P.; Jan. R.

1996-01-01

Based on the potential for decreasing costs of joining stiffeners to skin by laser beam welding, a fundamental research program was conducted to address the impediments identified during an initial study involving laser beam welding of aluminum-lithium alloys. Initial objectives of the program were the identification of governing mechanism responsible for process related porosity while establishing a multivariant relationship between process parameters and fusion zone geometry for laser beam welds of alloy 2195. A three-level fractional factorial experiment was conducted to establish quantitative relationships between primary laser beam processing parameters and critical weld attributes. Although process consistency appeared high for welds produced during partial completion of this study, numerous cracks on the top-surface of the welds were discovered during visual inspection and necessitated additional investigations concerning weld cracking. Two experiments were conducted to assess the effect of filler alloy additions on crack sensitivity: the first experiment was used to ascertain the effects of various filler alloys on cracking and the second experiment involved modification to process parameters for increasing filler metal dilution. Results indicated that filler alloys 4047 and 4145 showed promise for eliminating cracking.

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

Effects of developer exhaustion on DFL Contrast FV-58 and Kodak Insight dental films.

PubMed

de Carvalho, Fabiano Pachêco; da Silveira, M M F; Frazão, M A G; de Santana, S T; dos Anjos Pontual, M L

2011-09-01

The aim of this study was to compare the properties of the DFL Contrast FV-58 F-speed film (DFL Co., Rio de Janerio, Brazil) with the Kodak Insight E/F speed film (Eastman Kodak, Rochester, NY) in fresh and exhausted processing solutions. The parameters studied were the speed, average gradient and latitude. Five samples of each type of film were exposed under standardized conditions over 5 weeks. The films were developed in fresh and progressively exhausted processing solutions. Characteristic curves were constructed from values of optical density and radiation dose and were used to calculate the parameters. An analysis of variance was performed separately for film type and time. DFL Contrast FV-58 film has a speed and average gradient that is significantly higher than Insight film, whereas the values of latitude are lower. Exhausted processing solutions were not significant in the parameters studied. DFL Contrast FV-58 film has stable properties when exhausted manual processing solutions are used and can be recommended for use in dental practice, contributing to dose reduction.

Effects of developer exhaustion on DFL Contrast FV-58 and Kodak Insight dental films

PubMed Central

de Carvalho, FP; da Silveira, MMF; Frazão, MAG; de Santana, ST; dos Anjos Pontual, ML

2011-01-01

Objectives The aim of this study was to compare the properties of the DFL Contrast FV-58 F-speed film (DFL Co., Rio de Janerio, Brazil) with the Kodak Insight E/F speed film (Eastman Kodak, Rochester, NY) in fresh and exhausted processing solutions. The parameters studied were the speed, average gradient and latitude. Methods Five samples of each type of film were exposed under standardized conditions over 5 weeks. The films were developed in fresh and progressively exhausted processing solutions. Characteristic curves were constructed from values of optical density and radiation dose and were used to calculate the parameters. An analysis of variance was performed separately for film type and time. Results DFL Contrast FV-58 film has a speed and average gradient that is significantly higher than Insight film, whereas the values of latitude are lower. Exhausted processing solutions were not significant in the parameters studied. Conclusion DFL Contrast FV-58 film has stable properties when exhausted manual processing solutions are used and can be recommended for use in dental practice, contributing to dose reduction. PMID:21831975

Study of Material Densification of In718 in the Higher Throughput Parameter Regime

NASA Technical Reports Server (NTRS)

Cordner, Samuel

2016-01-01

Selective Laser Melting (SLM) is a powder bed fusion additive manufacturing process used increasingly in the aerospace industry to reduce the cost, weight, and fabrication time for complex propulsion components. Previous optimization studies for SLM using the Concept Laser M1 and M2 machines at NASA Marshall Space Flight Center have centered on machine default parameters. The objective of this project is to characterize how heat treatment affects density and porosity from a microscopic point of view. This is performs using higher throughput parameters (a previously unexplored region of the manufacturing operating envelope for this application) on material consolidation. Density blocks were analyzed to explore the relationship between build parameters (laser power, scan speed, and hatch spacing) and material consolidation (assessed in terms of density and porosity). The study also considers the impact of post-processing, specifically hot isostatic pressing and heat treatment, as well as deposition pattern on material consolidation in the higher energy parameter regime. Metallurgical evaluation of specimens will also be presented. This work will contribute to creating a knowledge base (understanding material behavior in all ranges of the AM equipment operating envelope) that is critical to transitioning AM from the custom low rate production sphere it currently occupies to the world of mass high rate production, where parts are fabricated at a rapid rate with confidence that they will meet or exceed all stringent functional requirements for spaceflight hardware. These studies will also provide important data on the sensitivity of material consolidation to process parameters that will inform the design and development of future flight articles using SLM.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process.

PubMed

Deng, Bo; Shi, Yaoyao; Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-31

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

PubMed Central

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

PubMed

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other

PubMed Central

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients’ medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD. PMID:28497080

Typecasting catchments: Classification, directionality, and the pursuit of universality

NASA Astrophysics Data System (ADS)

Smith, Tyler; Marshall, Lucy; McGlynn, Brian

2018-02-01

Catchment classification poses a significant challenge to hydrology and hydrologic modeling, restricting widespread transfer of knowledge from well-studied sites. The identification of important physical, climatological, or hydrologic attributes (to varying degrees depending on application/data availability) has traditionally been the focus for catchment classification. Classification approaches are regularly assessed with regard to their ability to provide suitable hydrologic predictions - commonly by transferring fitted hydrologic parameters at a data-rich catchment to a data-poor catchment deemed similar by the classification. While such approaches to hydrology's grand challenges are intuitive, they often ignore the most uncertain aspect of the process - the model itself. We explore catchment classification and parameter transferability and the concept of universal donor/acceptor catchments. We identify the implications of the assumption that the transfer of parameters between "similar" catchments is reciprocal (i.e., non-directional). These concepts are considered through three case studies situated across multiple gradients that include model complexity, process description, and site characteristics. Case study results highlight that some catchments are more successfully used as donor catchments and others are better suited as acceptor catchments. These results were observed for both black-box and process consistent hydrologic models, as well as for differing levels of catchment similarity. Therefore, we suggest that similarity does not adequately satisfy the underlying assumptions being made in parameter regionalization approaches regardless of model appropriateness. Furthermore, we suggest that the directionality of parameter transfer is an important factor in determining the success of parameter regionalization approaches.

On the biosorption, by brown seaweed, Lobophora variegata, of Ni(II) from aqueous solutions: equilibrium and thermodynamic studies.

PubMed

Basha, Shaik; Jaiswar, Santlal; Jha, Bhavanath

2010-09-01

The biosorption equilibrium isotherms of Ni(II) onto marine brown algae Lobophora variegata, which was chemically-modified by CaCl(2) were studied and modeled. To predict the biosorption isotherms and to determine the characteristic parameters for process design, twenty-three one-, two-, three-, four- and five-parameter isotherm models were applied to experimental data. The interaction among biosorbed molecules is attractive and biosorption is carried out on energetically different sites and is an endothermic process. The five-parameter Fritz-Schluender model gives the most accurate fit with high regression coefficient, R (2) (0.9911-0.9975) and F-ratio (118.03-179.96), and low standard error, SE (0.0902-0.0.1556) and the residual or sum of square error, SSE (0.0012-0.1789) values to all experimental data in comparison to other models. The biosorption isotherm models fitted the experimental data in the order: Fritz-Schluender (five-parameter) > Freundlich (two-parameter) > Langmuir (two-parameter) > Khan (three-parameter) > Fritz-Schluender (four-parameter). The thermodynamic parameters such as DeltaG (0), DeltaH (0) and DeltaS (0) have been determined, which indicates the sorption of Ni(II) onto L. variegata was spontaneous and endothermic in nature.

Study on voids of epoxy matrix composites sandwich structure parts

NASA Astrophysics Data System (ADS)

He, Simin; Wen, Youyi; Yu, Wenjun; Liu, Hong; Yue, Cheng; Bao, Jing

2017-03-01

Void is the most common tiny defect of composite materials. Porosity is closely related to composite structure property. The voids forming behaviour in the composites sandwich structural parts with the carbon fiber reinforced epoxy resin skins was researched by adjusting the manufacturing process parameters. The composites laminate with different porosities were prepared with the different process parameter. The ultrasonic non-destructive measurement method for the porosity was developed and verified through microscopic examination. The analysis results show that compaction pressure during the manufacturing process had influence on the porosity in the laminate area. Increasing the compaction pressure and compaction time will reduce the porosity of the laminates. The bond-line between honeycomb core and carbon fiber reinforced epoxy resin skins were also analyzed through microscopic examination. The mechanical properties of sandwich structure composites were studied. The optimization process parameters and porosity ultrasonic measurement method for composites sandwich structure have been applied to the production of the composite parts.

Assessing heat treatment of chicken breast cuts by impedance spectroscopy.

PubMed

Schmidt, Franciny C; Fuentes, Ana; Masot, Rafael; Alcañiz, Miguel; Laurindo, João B; Barat, José M

2017-03-01

The aim of this work was to develop a new system based on impedance spectroscopy to assess the heat treatment of previously cooked chicken meat by two experiments; in the first, samples were cooked at different temperatures (from 60 to 90 ℃) until core temperature of the meat reached the water bath temperature. In the second approach, temperature was 80 ℃ and the samples were cooked for different times (from 5 to 55 min). Impedance was measured once samples had cooled. The examined processing parameters were the maximum temperature reached in thermal centre of the samples, weight loss, moisture and the integral of the temperature profile during the cooking-cooling process. The correlation between the processing parameters and impedance was studied by partial least square regressions. The models were able to predict the studied parameters. Our results are essential for developing a new system to control the technological, sensory and safety aspects of cooked meat products on the whole meat processing line.

Multiple-objective optimization in precision laser cutting of different thermoplastics

NASA Astrophysics Data System (ADS)

Tamrin, K. F.; Nukman, Y.; Choudhury, I. A.; Shirley, S.

2015-04-01

Thermoplastics are increasingly being used in biomedical, automotive and electronics industries due to their excellent physical and chemical properties. Due to the localized and non-contact process, use of lasers for cutting could result in precise cut with small heat-affected zone (HAZ). Precision laser cutting involving various materials is important in high-volume manufacturing processes to minimize operational cost, error reduction and improve product quality. This study uses grey relational analysis to determine a single optimized set of cutting parameters for three different thermoplastics. The set of the optimized processing parameters is determined based on the highest relational grade and was found at low laser power (200 W), high cutting speed (0.4 m/min) and low compressed air pressure (2.5 bar). The result matches with the objective set in the present study. Analysis of variance (ANOVA) is then carried out to ascertain the relative influence of process parameters on the cutting characteristics. It was found that the laser power has dominant effect on HAZ for all thermoplastics.

Electrocoagulation of wastewater from almond industry.

PubMed

Valero, David; Ortiz, Juan M; García, Vicente; Expósito, Eduardo; Montiel, Vicente; Aldaz, Antonio

2011-08-01

This work was carried out to study the treatment of almond industry wastewater by the electrocoagulation process. First of all, laboratory scale experiments were conducted in order to determine the effects of relevant wastewater characteristics such as conductivity and pH, as well as the process variables such as anode material, current density and operating time on the removal efficiencies of the total organic carbon (TOC) and the most representative analytical parameters. Next, the wastewater treatment process was scaled up to pre-industrial size using the best experimental conditions and parameters obtained at laboratory scale. Finally, economic parameters such as chemicals, energy consumption and sludge generation have been discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Flexible Pilot-Scale Setup for Real-Time Studies in Process Systems Engineering

ERIC Educational Resources Information Center

Panjapornpon, Chanin; Fletcher, Nathan; Soroush, Masoud

2006-01-01

This manuscript describes a flexible, pilot-scale setup that can be used for training students and carrying out research in process systems engineering. The setup allows one to study a variety of process systems engineering concepts such as design feasibility, design flexibility, control configuration selection, parameter estimation, process and…

Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

Process development for robust removal of aggregates using cation exchange chromatography in monoclonal antibody purification with implementation of quality by design.

PubMed

Xu, Zhihao; Li, Jason; Zhou, Joe X

2012-01-01

Aggregate removal is one of the most important aspects in monoclonal antibody (mAb) purification. Cation-exchange chromatography (CEX), a widely used polishing step in mAb purification, is able to clear both process-related impurities and product-related impurities. In this study, with the implementation of quality by design (QbD), a process development approach for robust removal of aggregates using CEX is described. First, resin screening studies were performed and a suitable CEX resin was chosen because of its relatively better selectivity and higher dynamic binding capacity. Second, a pH-conductivity hybrid gradient elution method for the CEX was established, and the risk assessment for the process was carried out. Third, a process characterization study was used to evaluate the impact of the potentially important process parameters on the process performance with respect to aggregate removal. Accordingly, a process design space was established. Aggregate level in load is the critical parameter. Its operating range is set at 0-3% and the acceptable range is set at 0-5%. Equilibration buffer is the key parameter. Its operating range is set at 40 ± 5 mM acetate, pH 5.0 ± 0.1, and acceptable range is set at 40 ± 10 mM acetate, pH 5.0 ± 0.2. Elution buffer, load mass, and gradient elution volume are non-key parameters; their operating ranges and acceptable ranges are equally set at 250 ± 10 mM acetate, pH 6.0 ± 0.2, 45 ± 10 g/L resin, and 10 ± 20% CV respectively. Finally, the process was scaled up 80 times and the impurities removal profiles were revealed. Three scaled-up runs showed that the size-exclusion chromatography (SEC) purity of the CEX pool was 99.8% or above and the step yield was above 92%, thereby proving that the process is both consistent and robust.

Numerical simulation of polyester coextrusion: Influence of the thermal parameters and the die geometry on interfacial instabilities

NASA Astrophysics Data System (ADS)

Mahdaoui, O.; Agassant, J.-F.; Laure, P.; Valette, R.; Silva, L.

2007-04-01

The polymer coextrusion process is a new method of sheet metal lining. It allows to substitute lacquers for steel protection in food packaging industry. The coextrusion process may exhibit flow instabilities at the interface between the two polymer layers. The objective of this study is to check the influence of processing and rheology parameters on the instabilities. Finite elements numerical simulations of the coextrusion allow to investigate various stable and instable flow configurations.

Size-related bioconcentration kinetics of hydrophobic chemicals in fish

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sijm, D.T.H.M.; Linde, A. van der

1994-12-31

Uptake and elimination of hydrophobic chemicals by fish can be regarded as passive diffusive transport processes. Diffusion coefficients, lipid/water partitioning, diffusion pathlenghts, concentration gradients and surface exchange areas are key parameters describing this bioconcentration distribution process. In the present study two of these parameters were studied: the influence of lipid/water partitioning was studied by using hydrophobic chemicals of different hydrophobicity, and the surface exchange area by using different sizes of fish. By using one species of fish it was assumed that all other parameters were kept constant. Seven age classes of fish were exposed to a series of hydrophobic, formore » five days, which was followed by a deputation phase lasting up to 6 months. Bioconcentration parameters, such as uptake and elimination rate constants, and bioconcentration factors were determined. Uptake of the hydrophobic compounds was compared to that of oxygen. Uptake and elimination rates were compared to weight and estimated (gill) exchange areas. The role of weight and its implications for extrapolations of bioconcentration parameters to other species and sizes will be discussed.« less

Characteristic evaluation of process parameters of friction stir welding of aluminium 2024 hybrid composites

NASA Astrophysics Data System (ADS)

Sadashiva, M.; Shivanand, H. K.; Vidyasagar, H. N.

2018-04-01

The Current work is aimed to investigate the effect of process parameters in friction stir welding of Aluminium 2024 base alloy and Aluminium 2024 matrix alloy reinforced with E Glass and Silicon Carbide reinforcements. The process involved a set of synthesis techniques incorporating stir casting methodology resulting in fabrication of the composite material. This composite material that is synthesized is then machined to obtain a plate of dimensions 100 mm * 50 mm * 6 mm. The plate is then friction stir welded at different set of parameters viz. the spindle speed of 600 rpm, 900 rpm and 1200 rpm and feed rate of 40 mm/min, 80 mm/min and 120 mm/min for analyzing the process capability. The study of the given set of parameters is predominantly important to understand the physics of the process that may lead to better properties of the joint, which is very much important in perspective to its use in advanced engineering applications, especially in aerospace domain that uses Aluminium 2024 alloy for wing and fuselage structures under tension.

Investigation on Effect of Material Hardness in High Speed CNC End Milling Process.

PubMed

Dhandapani, N V; Thangarasu, V S; Sureshkannan, G

2015-01-01

This research paper analyzes the effects of material properties on surface roughness, material removal rate, and tool wear on high speed CNC end milling process with various ferrous and nonferrous materials. The challenge of material specific decision on the process parameters of spindle speed, feed rate, depth of cut, coolant flow rate, cutting tool material, and type of coating for the cutting tool for required quality and quantity of production is addressed. Generally, decision made by the operator on floor is based on suggested values of the tool manufacturer or by trial and error method. This paper describes effect of various parameters on the surface roughness characteristics of the precision machining part. The prediction method suggested is based on various experimental analysis of parameters in different compositions of input conditions which would benefit the industry on standardization of high speed CNC end milling processes. The results show a basis for selection of parameters to get better results of surface roughness values as predicted by the case study results.

On the residual stress modeling of shot-peened AISI 4340 steel: finite element and response surface methods

NASA Astrophysics Data System (ADS)

Asgari, Ali; Dehestani, Pouya; Poruraminaie, Iman

2018-02-01

Shot peening is a well-known process in applying the residual stress on the surface of industrial parts. The induced residual stress improves fatigue life. In this study, the effects of shot peening parameters such as shot diameter, shot speed, friction coefficient, and the number of impacts on the applied residual stress will be evaluated. To assess these parameters effect, firstly the shot peening process has been simulated by finite element method. Then, effects of the process parameters on the residual stress have been evaluated by response surface method as a statistical approach. Finally, a strong model is presented to predict the maximum residual stress induced by shot peening process in AISI 4340 steel. Also, the optimum parameters for the maximum residual stress are achieved. The results indicate that effect of shot diameter on the induced residual stress is increased by increasing the shot speed. Also, enhancing the friction coefficient magnitude always cannot lead to increase in the residual stress.

Investigation on Effect of Material Hardness in High Speed CNC End Milling Process

PubMed Central

Dhandapani, N. V.; Thangarasu, V. S.; Sureshkannan, G.

2015-01-01

This research paper analyzes the effects of material properties on surface roughness, material removal rate, and tool wear on high speed CNC end milling process with various ferrous and nonferrous materials. The challenge of material specific decision on the process parameters of spindle speed, feed rate, depth of cut, coolant flow rate, cutting tool material, and type of coating for the cutting tool for required quality and quantity of production is addressed. Generally, decision made by the operator on floor is based on suggested values of the tool manufacturer or by trial and error method. This paper describes effect of various parameters on the surface roughness characteristics of the precision machining part. The prediction method suggested is based on various experimental analysis of parameters in different compositions of input conditions which would benefit the industry on standardization of high speed CNC end milling processes. The results show a basis for selection of parameters to get better results of surface roughness values as predicted by the case study results. PMID:26881267

Progressive freezing and sweating in a test unit

NASA Astrophysics Data System (ADS)

Ulrich, J.; Özoğuz, Y.

1990-01-01

Crystallization from melts is applied in several fields like waste water treatment, fruit juice or liquid food concentration and purification of organic chemicals. Investigations to improve the understanding, the performance and the control of the process have been carried out. The experimental unit used a vertical tube with a falling film on the outside. With an specially designed measuring technique process controlling parameters have been studied. The results demonstrate the dependency of those parameters upon each other and indicate the way to control the process by controlling the dominant parameter. This is the growth rate of the crystal coat. A further purification of the crystal layer can be achieved by introducing the procedure of sweating, which is a controlled partial melting of the crystal coat. Here again process parameters have been varied and results are presented. The strong effect upon the final purity of the product by an efficient executed sweating which is effectively tuned on the crystallization procedure should save crystallization steps, energy and time.

Mathematical modeling of heat treatment processes conserving biological activity of plant bioresources

NASA Astrophysics Data System (ADS)

Rodionova, N. S.; Popov, E. S.; Pozhidaeva, E. A.; Pynzar, S. S.; Ryaskina, L. O.

2018-05-01

The aim of this study is to develop a mathematical model of the heat exchange process of LT-processing to estimate the dynamics of temperature field changes and optimize the regime parameters, due to the non-stationarity process, the physicochemical and thermophysical properties of food systems. The application of LT-processing, based on the use of low-temperature modes in thermal culinary processing of raw materials with preliminary vacuum packaging in a polymer heat- resistant film is a promising trend in the development of technics and technology in the catering field. LT-processing application of food raw materials guarantees the preservation of biologically active substances in food environments, which are characterized by a certain thermolability, as well as extend the shelf life and high consumer characteristics of food systems that are capillary-porous bodies. When performing the mathematical modeling of the LT-processing process, the packet of symbolic mathematics “Maple” was used, as well as the mathematical packet flexPDE that uses the finite element method for modeling objects with distributed parameters. The processing of experimental results was evaluated with the help of the developed software in the programming language Python 3.4. To calculate and optimize the parameters of the LT processing process of polycomponent food systems, the differential equation of non-stationary thermal conductivity was used, the solution of which makes it possible to identify the temperature change at any point of the solid at different moments. The present study specifies data on the thermophysical characteristics of the polycomponent food system based on plant raw materials, with the help of which the physico-mathematical model of the LT- processing process has been developed. The obtained mathematical model allows defining of the dynamics of the temperature field in different sections of the LT-processed polycomponent food systems on the basis of calculating the evolution profiles of temperature fields, which enable one to analyze the efficiency of the regime parameters of heat treatment.

Simulation study of spheroidal dust gains charging: Applicable to dust grain alignment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zahed, H.; Sobhanian, S.; Mahmoodi, J.

2006-09-15

The charging process of nonspherical dust grains in an unmagnetized plasma as well as in the presence of a magnetic field is studied. It is shown that unlike the spherical dust grain, due to nonhomogeneity of charge distribution on the spheroidal dust surface, the resultant electric forces on electrons and ions are different. This process produces some surface charge density gradient on the nonspherical grain surface. Effects of a magnetic field and other plasma parameters on the properties of the dust particulate are studied. It has been shown that the alignment direction could be changed or even reversed with themore » magnetic field and plasma parameters. Finally, the charge distribution on the spheroidal grain surface is studied for different ambient parameters including plasma temperature, neutral collision frequency, and the magnitude of the magnetic field.« less

Research on a Defects Detection Method in the Ferrite Phase Shifter Cementing Process Based on a Multi-Sensor Prognostic and Health Management (PHM) System.

PubMed

Wan, Bo; Fu, Guicui; Li, Yanruoyue; Zhao, Youhu

2016-08-10

The cementing manufacturing process of ferrite phase shifters has the defect that cementing strength is insufficient and fractures always appear. A detection method of these defects was studied utilizing the multi-sensors Prognostic and Health Management (PHM) theory. Aiming at these process defects, the reasons that lead to defects are analyzed in this paper. In the meanwhile, the key process parameters were determined and Differential Scanning Calorimetry (DSC) tests during the cure process of resin cementing were carried out. At the same time, in order to get data on changing cementing strength, multiple-group cementing process tests of different key process parameters were designed and conducted. A relational model of cementing strength and cure temperature, time and pressure was established, by combining data of DSC and process tests as well as based on the Avrami formula. Through sensitivity analysis for three process parameters, the on-line detection decision criterion and the process parameters which have obvious impact on cementing strength were determined. A PHM system with multiple temperature and pressure sensors was established on this basis, and then, on-line detection, diagnosis and control for ferrite phase shifter cementing process defects were realized. It was verified by subsequent process that the on-line detection system improved the reliability of the ferrite phase shifter cementing process and reduced the incidence of insufficient cementing strength defects.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Hongyi; Li, Yang; Zeng, Danielle

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. Formore » multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.« less

Effect of microwave argon plasma on the glycosidic and hydrogen bonding system of cotton cellulose.

PubMed

Prabhu, S; Vaideki, K; Anitha, S

2017-01-20

Cotton fabric was processed with microwave (Ar) plasma to alter its hydrophilicity. The process parameters namely microwave power, process gas pressure and processing time were optimized using Box-Behnken method available in the Design Expert software. It was observed that certain combinations of process parameters improved existing hydrophilicity while the other combinations decreased it. ATR-FTIR spectral analysis was used to identify the strain induced in inter chain, intra chain, and inter sheet hydrogen bond and glycosidic covalent bond due to plasma treatment. X-ray diffraction (XRD) studies was used to analyze the effect of plasma on unit cell parameters and degree of crystallinity. Fabric surface etching was identified using FESEM analysis. Thus, it can be concluded that the increase/decrease in the hydrophilicity of the plasma treated fabric was due to these structural and physical changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimating Function Approaches for Spatial Point Processes

NASA Astrophysics Data System (ADS)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting second-order intensity function of spatial point processes. However, the original second-order quasi-likelihood is barely feasible due to the intense computation and high memory requirement needed to solve a large linear system. Motivated by the existence of geometric regular patterns in the stationary point processes, we find a lower dimension representation of the optimal weight function and propose a reduced second-order quasi-likelihood approach. Through a simulation study, we show that the proposed method not only demonstrates superior performance in fitting the clustering parameter but also merits in the relaxation of the constraint of the tuning parameter, H. Third, we studied the quasi-likelihood type estimating funciton that is optimal in a certain class of first-order estimating functions for estimating the regression parameter in spatial point process models. Then, by using a novel spectral representation, we construct an implementation that is computationally much more efficient and can be applied to more general setup than the original quasi-likelihood method.

Surface Modification of Micro-Alloyed High-Strength Low-Alloy Steel by Controlled TIG Arcing Process

NASA Astrophysics Data System (ADS)

Ghosh, P. K.; Kumar, Ravindra

2015-02-01

Surface modification of micro-alloyed HSLA steel plate has been carried out by autogenous conventional and pulse current tungsten inert gas arcing (TIGA) processes at different welding parameters while the energy input was kept constant. At a given energy input the influence of pulse parameters on the characteristics of surface modification has been studied in case of employing single and multi-run procedure. The role of pulse parameters has been studied by considering their summarized influence defined by a factor Φ. The variation in Φ and pulse frequency has been found to significantly affect the thermal behavior of fusion and accordingly the width and penetration of the modified region along with its microstructure, hardness and wear characteristics. It is found that pulsed TIGA is relatively more advantageous over the conventional TIGA process, as it leads to higher hardness, improved wear resistance, and a better control over surface characteristics.

Evaluation of laser cutting process with auxiliary gas pressure by soft computing approach

NASA Astrophysics Data System (ADS)

Lazov, Lyubomir; Nikolić, Vlastimir; Jovic, Srdjan; Milovančević, Miloš; Deneva, Heristina; Teirumenieka, Erika; Arsic, Nebojsa

2018-06-01

Evaluation of the optimal laser cutting parameters is very important for the high cut quality. This is highly nonlinear process with different parameters which is the main challenge in the optimization process. Data mining methodology is one of most versatile method which can be used laser cutting process optimization. Support vector regression (SVR) procedure is implemented since it is a versatile and robust technique for very nonlinear data regression. The goal in this study was to determine the optimal laser cutting parameters to ensure robust condition for minimization of average surface roughness. Three cutting parameters, the cutting speed, the laser power, and the assist gas pressure, were used in the investigation. As a laser type TruLaser 1030 technological system was used. Nitrogen as an assisted gas was used in the laser cutting process. As the data mining method, support vector regression procedure was used. Data mining prediction accuracy was very high according the coefficient (R2) of determination and root mean square error (RMSE): R2 = 0.9975 and RMSE = 0.0337. Therefore the data mining approach could be used effectively for determination of the optimal conditions of the laser cutting process.

Contributions to ultrasound monitoring of the process of milk curdling.

PubMed

Jiménez, Antonio; Rufo, Montaña; Paniagua, Jesús M; Crespo, Abel T; Guerrero, M Patricia; Riballo, M José

2017-04-01

Ultrasound evaluation permits the state of milk being curdled to be determined quickly and cheaply, thus satisfying the demands faced by today's dairy product producers. This paper describes the non-invasive ultrasonic method of in situ monitoring the changing physical properties of milk during the renneting process. The basic objectives of the study were, on the one hand, to confirm the usefulness of conventional non-destructive ultrasonic testing (time-of-flight and attenuation of the ultrasound waves) in monitoring the process in the case of ewe's milk, and, on the other, to include other ultrasound parameters which have not previously been considered in studies on this topic, in particular, parameters provided by the Fast Fourier Transform technique. The experimental study was carried out in a dairy industry environment on four 52-l samples of raw milk in which were immersed 500kHz ultrasound transducers. Other physicochemical parameters of the raw milk (pH, dry matter, protein, Gerber fat test, and lactose) were measured, as also were the pH and temperature of the curdled samples simultaneously with the ultrasound tests. Another contribution of this study is the linear correlation analysis of the aforementioned ultrasound parameters and the physicochemical properties of the curdled milk. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of implant drilling parameters for pilot and twist drills on temperature rise in bone analog and alveolar bones.

PubMed

Chen, Yung-Chuan; Hsiao, Chih-Kun; Ciou, Ji-Sih; Tsai, Yi-Jung; Tu, Yuan-Kun

2016-11-01

This study concerns the effects of different drilling parameters of pilot drills and twist drills on the temperature rise of alveolar bones during dental implant procedures. The drilling parameters studied here include the feed rate and rotation speed of the drill. The bone temperature distribution was analyzed through experiments and numerical simulations of the drilling process. In this study, a three dimensional (3D) elasto-plastic dynamic finite element model (DFEM) was proposed to investigate the effects of drilling parameters on the bone temperature rise. In addition, the FE model is validated with drilling experiments on artificial human bones and porcine alveolar bones. The results indicate that 3D DFEM can effectively simulate the bone temperature rise during the drilling process. During the drilling process with pilot drills or twist drills, the maximum bone temperature occurred in the region of the cancellous bones close to the cortical bones. The feed rate was one of the important factors affecting the time when the maximum bone temperature occurred. Our results also demonstrate that the elevation of bone temperature was reduced as the feed rate increased and the drill speed decreased, which also effectively reduced the risk region of osteonecrosis. These findings can serve as a reference for dentists in choosing drilling parameters for dental implant surgeries. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Sensitivity of Austempering Heat Treatment of Ductile Irons to Changes in Process Parameters

NASA Astrophysics Data System (ADS)

Boccardo, A. D.; Dardati, P. M.; Godoy, L. A.; Celentano, D. J.

2018-06-01

Austempered ductile iron (ADI) is frequently obtained by means of a three-step austempering heat treatment. The parameters of this process play a crucial role on the microstructure of the final product. This paper considers the influence of some process parameters ( i.e., the initial microstructure of ductile iron and the thermal cycle) on key features of the heat treatment (such as minimum required time for austenitization and austempering and microstructure of the final product). A computational simulation of the austempering heat treatment is reported in this work, which accounts for a coupled thermo-metallurgical behavior in terms of the evolution of temperature at the scale of the part being investigated (the macroscale) and the evolution of phases at the scale of microconstituents (the microscale). The paper focuses on the sensitivity of the process by looking at a sensitivity index and scatter plots. The sensitivity indices are determined by using a technique based on the variance of the output. The results of this study indicate that both the initial microstructure and the thermal cycle parameters play a key role in the production of ADI. This work also provides a guideline to help selecting values of the appropriate process parameters to obtain parts with a required microstructural characteristic.

In-depth analysis and characterization of a dual damascene process with respect to different CD

NASA Astrophysics Data System (ADS)

Krause, Gerd; Hofmann, Detlef; Habets, Boris; Buhl, Stefan; Gutsch, Manuela; Lopez-Gomez, Alberto; Kim, Wan-Soo; Thrun, Xaver

2018-03-01

In a 200 mm high volume environment, we studied data from a dual damascene process. Dual damascene is a combination of lithography, etch and CMP that is used to create copper lines and contacts in one single step. During these process steps, different metal CD are measured by different measurement methods. In this study, we analyze the key numbers of the different measurements after different process steps and develop simple models to predict the electrical behavior* . In addition, radial profiles have been analyzed of both inline measurement parameters and electrical parameters. A matching method was developed based on inline and electrical data. Finally, correlation analysis for radial signatures is presented that can be used to predict excursions in electrical signatures.

Warpage analysis on thin shell part using glowworm swarm optimisation (GSO)

NASA Astrophysics Data System (ADS)

Zulhasif, Z.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

The Autodesk Moldflow Insight (AMI) software was used in this study to focuses on the analysis in plastic injection moulding process associate the input parameter and output parameter. The material used in this study is Acrylonitrile Butadiene Styrene (ABS) as the moulded material to produced the plastic part. The MATLAB sortware is a method was used to find the best setting parameter. The variables was selected in this study were melt temperature, packing pressure, coolant temperature and cooling time.

Modelling the Cast Component Weight in Hot Chamber Die Casting using Combined Taguchi and Buckingham's π Approach

NASA Astrophysics Data System (ADS)

Singh, Rupinder

2018-02-01

Hot chamber (HC) die casting process is one of the most widely used commercial processes for the casting of low temperature metals and alloys. This process gives near-net shape product with high dimensional accuracy. However in actual field environment the best settings of input parameters is often conflicting as the shape and size of the casting changes and one have to trade off among various output parameters like hardness, dimensional accuracy, casting defects, microstructure etc. So for online inspection of the cast components properties (without affecting the production line) the weight measurement has been established as one of the cost effective method (as the difference in weight of sound and unsound casting reflects the possible casting defects) in field environment. In the present work at first stage the effect of three input process parameters (namely: pressure at 2nd phase in HC die casting; metal pouring temperature and die opening time) has been studied for optimizing the cast component weight `W' as output parameter in form of macro model based upon Taguchi L9 OA. After this Buckingham's π approach has been applied on Taguchi based macro model for the development of micro model. This study highlights the Taguchi-Buckingham based combined approach as a case study (for conversion of macro model into micro model) by identification of optimum levels of input parameters (based on Taguchi approach) and development of mathematical model (based on Buckingham's π approach). Finally developed mathematical model can be used for predicting W in HC die casting process with more flexibility. The results of study highlights second degree polynomial equation for predicting cast component weight in HC die casting and suggest that pressure at 2nd stage is one of the most contributing factors for controlling the casting defect/weight of casting.

Multiobjective optimization in structural design with uncertain parameters and stochastic processes

NASA Technical Reports Server (NTRS)

Rao, S. S.

1984-01-01

The application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes is studied. The design of a cantilever beam with a tip mass subjected to a stochastic base excitation is considered for illustration. Several of the problem parameters are assumed to be random variables and the structural mass, fatigue damage, and negative of natural frequency of vibration are considered for minimization. The solution of this three-criteria design problem is found by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It is observed that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions. The procedures used in the present investigation are expected to be useful in the design of general dynamic systems involving uncertain parameters, stochastic process, and multiple objectives.

Color separation in forensic image processing using interactive differential evolution.

PubMed

Mushtaq, Harris; Rahnamayan, Shahryar; Siddiqi, Areeb

2015-01-01

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes. © 2014 American Academy of Forensic Sciences.

Study on reservoir time-varying design flood of inflow based on Poisson process with time-dependent parameters

NASA Astrophysics Data System (ADS)

Li, Jiqing; Huang, Jing; Li, Jianchang

2018-06-01

The time-varying design flood can make full use of the measured data, which can provide the reservoir with the basis of both flood control and operation scheduling. This paper adopts peak over threshold method for flood sampling in unit periods and Poisson process with time-dependent parameters model for simulation of reservoirs time-varying design flood. Considering the relationship between the model parameters and hypothesis, this paper presents the over-threshold intensity, the fitting degree of Poisson distribution and the design flood parameters are the time-varying design flood unit period and threshold discriminant basis, deduced Longyangxia reservoir time-varying design flood process at 9 kinds of design frequencies. The time-varying design flood of inflow is closer to the reservoir actual inflow conditions, which can be used to adjust the operating water level in flood season and make plans for resource utilization of flood in the basin.

On the Modeling of Vacuum Arc Remelting Process in Titanium Alloys

NASA Astrophysics Data System (ADS)

Patel, Ashish; Fiore, Daniel

2016-07-01

Mathematical modeling is routinely used in the process development and production of advanced aerospace alloys to gain greater insight into the effect of process parameters on final properties. This article describes the application of a 2-D mathematical VAR model presented at previous LMPC meetings. The impact of process parameters on melt pool geometry, solidification behavior, fluid-flow and chemistry in a Ti-6Al-4V ingot is discussed. Model predictions are validated against published data from a industrial size ingot, and results of a parametric study on particle dissolution are also discussed.

A Design of Experiment approach to predict product and process parameters for a spray dried influenza vaccine.

PubMed

Kanojia, Gaurav; Willems, Geert-Jan; Frijlink, Henderik W; Kersten, Gideon F A; Soema, Peter C; Amorij, Jean-Pierre

2016-09-25

Spray dried vaccine formulations might be an alternative to traditional lyophilized vaccines. Compared to lyophilization, spray drying is a fast and cheap process extensively used for drying biologicals. The current study provides an approach that utilizes Design of Experiments for spray drying process to stabilize whole inactivated influenza virus (WIV) vaccine. The approach included systematically screening and optimizing the spray drying process variables, determining the desired process parameters and predicting product quality parameters. The process parameters inlet air temperature, nozzle gas flow rate and feed flow rate and their effect on WIV vaccine powder characteristics such as particle size, residual moisture content (RMC) and powder yield were investigated. Vaccine powders with a broad range of physical characteristics (RMC 1.2-4.9%, particle size 2.4-8.5μm and powder yield 42-82%) were obtained. WIV showed no significant loss in antigenicity as revealed by hemagglutination test. Furthermore, descriptive models generated by DoE software could be used to determine and select (set) spray drying process parameter. This was used to generate a dried WIV powder with predefined (predicted) characteristics. Moreover, the spray dried vaccine powders retained their antigenic stability even after storage for 3 months at 60°C. The approach used here enabled the generation of a thermostable, antigenic WIV vaccine powder with desired physical characteristics that could be potentially used for pulmonary administration. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Friction Stir Welding (FSW) of Aged CuCrZr Alloy Plates

NASA Astrophysics Data System (ADS)

Jha, Kaushal; Kumar, Santosh; Nachiket, K.; Bhanumurthy, K.; Dey, G. K.

2018-01-01

Friction Stir Welding (FSW) of Cu-0.80Cr-0.10Zr (in wt pct) alloy under aged condition was performed to study the effects of process parameters on microstructure and properties of the joint. FSW was performed over a wide range of process parameters, like tool-rotation speed (from 800 to 1200 rpm) and tool-travel speed (from 40 to 100 mm/min), and the resulting thermal cycles were recorded on both sides (advancing and retreating) of the joint. The joints were characterized for their microstructure and tensile properties. The welding process resulted in a sound and defect-free weld joint, over the entire range of the process parameters used in this study. Microstructure of the stir zone showed fine and equiaxed grains, the scale of which varied with FSW process parameters. Grain size in the stir zone showed direct correlation with tool rotation and inverse correlation with tool-travel speed. Tensile strength of the weld joints was ranging from 225 to 260 MPa, which is substantially lower than that of the parent metal under aged condition ( 400 MPa), but superior to that of the parent material under annealed condition ( 220 MPa). Lower strength of the FSW joint than that of the parent material under aged condition can be attributed to dissolution of the precipitates in the stir zone and TMAZ. These results are presented and discussed in this paper.

A comparative study of electrochemical machining process parameters by using GA and Taguchi method

NASA Astrophysics Data System (ADS)

Soni, S. K.; Thomas, B.

2017-11-01

In electrochemical machining quality of machined surface strongly depend on the selection of optimal parameter settings. This work deals with the application of Taguchi method and genetic algorithm using MATLAB to maximize the metal removal rate and minimize the surface roughness and overcut. In this paper a comparative study is presented for drilling of LM6 AL/B4C composites by comparing the significant impact of numerous machining process parameters such as, electrolyte concentration (g/l),machining voltage (v),frequency (hz) on the response parameters (surface roughness, material removal rate and over cut). Taguchi L27 orthogonal array was chosen in Minitab 17 software, for the investigation of experimental results and also multiobjective optimization done by genetic algorithm is employed by using MATLAB. After obtaining optimized results from Taguchi method and genetic algorithm, a comparative results are presented.

Optimizing operating parameters of a honeycomb zeolite rotor concentrator for processing TFT-LCD volatile organic compounds with competitive adsorption characteristics.

PubMed

Lin, Yu-Chih; Chang, Feng-Tang

2009-05-30

In this study, we attempted to enhance the removal efficiency of a honeycomb zeolite rotor concentrator (HZRC), operated at optimal parameters, for processing TFT-LCD volatile organic compounds (VOCs) with competitive adsorption characteristics. The results indicated that when the HZRC processed a VOCs stream of mixed compounds, compounds with a high boiling point take precedence in the adsorption process. In addition, existing compounds with a low boiling point adsorbed onto the HZRC were also displaced by the high-boiling-point compounds. In order to achieve optimal operating parameters for high VOCs removal efficiency, results suggested controlling the inlet velocity to <1.5m/s, reducing the concentration ratio to 8 times, increasing the desorption temperature to 200-225 degrees C, and setting the rotation speed to 6.5rpm.

Design of a robust fuzzy controller for the arc stability of CO(2) welding process using the Taguchi method.

PubMed

Kim, Dongcheol; Rhee, Sehun

2002-01-01

CO(2) welding is a complex process. Weld quality is dependent on arc stability and minimizing the effects of disturbances or changes in the operating condition commonly occurring during the welding process. In order to minimize these effects, a controller can be used. In this study, a fuzzy controller was used in order to stabilize the arc during CO(2) welding. The input variable of the controller was the Mita index. This index estimates quantitatively the arc stability that is influenced by many welding process parameters. Because the welding process is complex, a mathematical model of the Mita index was difficult to derive. Therefore, the parameter settings of the fuzzy controller were determined by performing actual control experiments without using a mathematical model of the controlled process. The solution, the Taguchi method was used to determine the optimal control parameter settings of the fuzzy controller to make the control performance robust and insensitive to the changes in the operating conditions.

Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development

DOE PAGES

Xu, Hongyi; Li, Yang; Zeng, Danielle

2017-01-02

Process integration and optimization is the key enabler of the Integrated Computational Materials Engineering (ICME) of carbon fiber composites. In this paper, automated workflows are developed for two types of composites: Sheet Molding Compounds (SMC) short fiber composites, and multi-layer unidirectional (UD) composites. For SMC, the proposed workflow integrates material processing simulation, microstructure representation volume element (RVE) models, material property prediction and structure preformation simulation to enable multiscale, multidisciplinary analysis and design. Processing parameters, microstructure parameters and vehicle subframe geometry parameters are defined as the design variables; the stiffness and weight of the structure are defined as the responses. Formore » multi-layer UD structure, this work focuses on the discussion of different design representation methods and their impacts on the optimization performance. Challenges in ICME process integration and optimization are also summarized and highlighted. Two case studies are conducted to demonstrate the integrated process and its application in optimization.« less

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

Interactions of solutes and streambed sediment: 2. A dynamic analysis of coupled hydrologic and chemical processes that determine solute transport

USGS Publications Warehouse

Bencala, Kenneth E.

1984-01-01

Solute transport in streams is determined by the interaction of physical and chemical processes. Data from an injection experiment for chloride and several cations indicate significant influence of solutestreambed processes on transport in a mountain stream. These data are interpreted in terms of transient storage processes for all tracers and sorption processes for the cations. Process parameter values are estimated with simulations based on coupled quasi-two-dimensional transport and first-order mass transfer sorption. Comparative simulations demonstrate the relative roles of the physical and chemical processes in determining solute transport. During the first 24 hours of the experiment, chloride concentrations were attenuated relative to expected plateau levels. Additional attenuation occurred for the sorbing cation strontium. The simulations account for these storage processes. Parameter values determined by calibration compare favorably with estimates from other studies in mountain streams. Without further calibration, the transport of potassium and lithium is adequately simulated using parameters determined in the chloride-strontium simulation and with measured cation distribution coefficients.

Grinding, Machining Morphological Studies on C/SiC Composites

NASA Astrophysics Data System (ADS)

Xiao, Chun-fang; Han, Bing

2018-05-01

C/SiC composite is a typical material difficult to machine. It is hard and brittle. In machining, the cutting force is large, the material removal rate is low, the edge is prone to collapse, and the tool wear is serious. In this paper, the grinding of C/Si composites material along the direction of fiber distribution is studied respectively. The surface microstructure and mechanical properties of C/SiC composites processed by ultrasonic machining were evaluated. The change of surface quality with the change of processing parameters has also been studied. By comparing the performances of conventional grinding and ultrasonic grinding, the surface roughness and functional characteristics of the material can be improved by optimizing the processing parameters.

Dependencies and Ill-designed Parameters Within High-speed Videoendoscopy and Acoustic Signal Analysis.

PubMed

Schlegel, Patrick; Stingl, Michael; Kunduk, Melda; Kniesburges, Stefan; Bohr, Christopher; Döllinger, Michael

2018-05-31

The phonatory process is often judged during sustained phonation by analyzing the acoustic voice signal and the vocal fold vibrations. Many formulas and parameters have been suggested for qualifying the characteristics of the acoustic signal and the vocal fold vibrations during sustained phonation. These parameters are directly computed from the acoustic signal and the endoscopic glottal area waveform (GAW). The GAW is calculated from laryngeal high-speed videoendoscopy (HSV) recordings and describes the increase and decrease of the glottal area during the phonation process, that is, the opening and closing of the two oscillating vocal folds over time. However, some of the parameters have strong mathematical dependencies with one another and some are ill-defined. The purpose of this study is to identify mathematical dependencies between parameters with the aim of reducing their numbers and suggesting which parameters may best describe the properties of the GAW and the acoustical signal. In this preliminary investigation, 20 frequently used parameters are examined: 10 GAW only and 10 both GAW and acoustic parameters. In total 13 parameters can be neglected because of mathematical dependencies. In addition, nine of these parameters show problematic features that range from unexpected behavior to ill definition. Reducing the number of parameters appears to be necessary to standardize vocal fold function analysis. This may lead to better comparability of research results from different studies. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Comparative Assessment of Cutting Inserts and Optimization during Hard Turning: Taguchi-Based Grey Relational Analysis

NASA Astrophysics Data System (ADS)

Venkata Subbaiah, K.; Raju, Ch.; Suresh, Ch.

2017-08-01

The present study aims to compare the conventional cutting inserts with wiper cutting inserts during the hard turning of AISI 4340 steel at different workpiece hardness. Type of insert, hardness, cutting speed, feed, and depth of cut are taken as process parameters. Taguchi’s L18 orthogonal array was used to conduct the experimental tests. Parametric analysis carried in order to know the influence of each process parameter on the three important Surface Roughness Characteristics (Ra, Rz, and Rt) and Material Removal Rate. Taguchi based Grey Relational Analysis (GRA) used to optimize the process parameters for individual response and multi-response outputs. Additionally, the analysis of variance (ANOVA) is also applied to identify the most significant factor.

Important parameters for smoke plume rise simulation with Daysmoke

Treesearch

L. Liu; G.L. Achtemeier; S.L. Goodrick; W. Jackson

2010-01-01

Daysmoke is a local smoke transport model and has been used to provide smoke plume rise information. It includes a large number of parameters describing the dynamic and stochastic processes of particle upward movement, fallout, fluctuation, and burn emissions. This study identifies the important parameters for Daysmoke simulations of plume rise and seeks to understand...

Warpage optimization on a mobile phone case using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Lee, X. N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Shazzuan, S.

2017-09-01

Plastic injection moulding is a popular manufacturing method not only it is reliable, but also efficient and cost saving. It able to produce plastic part with detailed features and complex geometry. However, defects in injection moulding process degrades the quality and aesthetic of the injection moulded product. The most common defect occur in the process is warpage. Inappropriate process parameter setting of injection moulding machine is one of the reason that leads to the occurrence of warpage. The aims of this study were to improve the quality of injection moulded part by investigating the optimal parameters in minimizing warpage using Response Surface Methodology (RSM). Subsequent to this, the most significant parameter was identified and recommended parameters setting was compared with the optimized parameter setting using RSM. In this research, the mobile phone case was selected as case study. The mould temperature, melt temperature, packing pressure, packing time and cooling time were selected as variables whereas warpage in y-direction was selected as responses in this research. The simulation was carried out by using Autodesk Moldflow Insight 2012. In addition, the RSM was performed by using Design Expert 7.0. The warpage in y direction recommended by RSM were reduced by 70 %. RSM performed well in solving warpage issue.

Exemplifying the Effects of Parameterization Shortcomings in the Numerical Simulation of Geological Energy and Mass Storage

NASA Astrophysics Data System (ADS)

Dethlefsen, Frank; Tilmann Pfeiffer, Wolf; Schäfer, Dirk

2016-04-01

Numerical simulations of hydraulic, thermal, geomechanical, or geochemical (THMC-) processes in the subsurface have been conducted for decades. Often, such simulations are commenced by applying a parameter set that is as realistic as possible. Then, a base scenario is calibrated on field observations. Finally, scenario simulations can be performed, for instance to forecast the system behavior after varying input data. In the context of subsurface energy and mass storage, however, these model calibrations based on field data are often not available, as these storage actions have not been carried out so far. Consequently, the numerical models merely rely on the parameter set initially selected, and uncertainties as a consequence of a lack of parameter values or process understanding may not be perceivable, not mentioning quantifiable. Therefore, conducting THMC simulations in the context of energy and mass storage deserves a particular review of the model parameterization with its input data, and such a review so far hardly exists to the required extent. Variability or aleatory uncertainty exists for geoscientific parameter values in general, and parameters for that numerous data points are available, such as aquifer permeabilities, may be described statistically thereby exhibiting statistical uncertainty. In this case, sensitivity analyses for quantifying the uncertainty in the simulation resulting from varying this parameter can be conducted. There are other parameters, where the lack of data quantity and quality implies a fundamental changing of ongoing processes when such a parameter value is varied in numerical scenario simulations. As an example for such a scenario uncertainty, varying the capillary entry pressure as one of the multiphase flow parameters can either allow or completely inhibit the penetration of an aquitard by gas. As the last example, the uncertainty of cap-rock fault permeabilities and consequently potential leakage rates of stored gases into shallow compartments are regarded as recognized ignorance by the authors of this study, as no realistic approach exists to determine this parameter and values are best guesses only. In addition to these aleatory uncertainties, an equivalent classification is possible for rating epistemic uncertainties describing the degree of understanding processes such as the geochemical and hydraulic effects following potential gas intrusions from deeper reservoirs into shallow aquifers. As an outcome of this grouping of uncertainties, prediction errors of scenario simulations can be calculated by sensitivity analyses, if the uncertainties are identified as statistical. However, if scenario uncertainties exist or even recognized ignorance has to be attested to a parameter or a process in question, the outcomes of simulations mainly depend on the decision of the modeler by choosing parameter values or by interpreting the occurring of processes. In that case, the informative value of numerical simulations is limited by ambiguous simulation results, which cannot be refined without improving the geoscientific database through laboratory or field studies on a longer term basis, so that the effects of the subsurface use may be predicted realistically. This discussion, amended by a compilation of available geoscientific data to parameterize such simulations, will be presented in this study.

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Impact of parameter fluctuations on the performance of ethanol precipitation in production of Re Du Ning Injections, based on HPLC fingerprints and principal component analysis.

PubMed

Sun, Li-Qiong; Wang, Shu-Yao; Li, Yan-Jing; Wang, Yong-Xiang; Wang, Zhen-Zhong; Huang, Wen-Zhe; Wang, Yue-Sheng; Bi, Yu-An; Ding, Gang; Xiao, Wei

2016-01-01

The present study was designed to determine the relationships between the performance of ethanol precipitation and seven process parameters in the ethanol precipitation process of Re Du Ning Injections, including concentrate density, concentrate temperature, ethanol content, flow rate and stir rate in the addition of ethanol, precipitation time, and precipitation temperature. Under the experimental and simulated production conditions, a series of precipitated resultants were prepared by changing these variables one by one, and then examined by HPLC fingerprint analyses. Different from the traditional evaluation model based on single or a few constituents, the fingerprint data of every parameter fluctuation test was processed with Principal Component Analysis (PCA) to comprehensively assess the performance of ethanol precipitation. Our results showed that concentrate density, ethanol content, and precipitation time were the most important parameters that influence the recovery of active compounds in precipitation resultants. The present study would provide some reference for pharmaceutical scientists engaged in research on pharmaceutical process optimization and help pharmaceutical enterprises adapt a scientific and reasonable cost-effective approach to ensure the batch-to-batch quality consistency of the final products. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

An investigation of desalination by nanofiltration, reverse osmosis and integrated (hybrid NF/RO) membranes employed in brackish water treatment.

PubMed

Talaeipour, M; Nouri, J; Hassani, A H; Mahvi, A H

2017-01-01

As an appropriate tool, membrane process is used for desalination of brackish water, in the production of drinking water. The present study aims to investigate desalination processes of brackish water of Qom Province in Iran. This study was carried out at the central laboratory of Water and Wastewater Company of the studied area. To this aim, membrane processes, including nanofiltration (NF) and reverse osmosis (RO), separately and also their hybrid process were applied. Moreover, water physical and chemical parameters, including salinity, total dissolved solids (TDS), electric conductivity (EC), Na +1 and Cl -1 were also measured. Afterward, the rejection percent of each parameter was investigated and compared using nanofiltration and reverse osmosis separately and also by their hybrid process. The treatment process was performed by Luna domestic desalination device, which its membrane was replaced by two NF90 and TW30 membranes for nanofiltration and reverse osmosis processes, respectively. All collected brackish water samples were fed through membranes NF90-2540, TW30-1821-100(RO) and Hybrid (NF/RO) which were installed on desalination household scale pilot (Luna water 100GPD). Then, to study the effects of pressure on permeable quality of membranes, the simulation software model ROSA was applied. Results showed that percent of the salinity rejection was recorded as 50.21%; 72.82 and 78.56% in NF, RO and hybrid processes, respectively. During the study, in order to simulate the performance of nanofiltartion, reverse osmosis and hybrid by pressure drive, reverse osmosis system analysis (ROSA) model was applied. The experiments were conducted at performance three methods of desalination to remove physic-chemical parameters as percentage of rejections in the pilot plant are: in the NF system the salinity 50.21, TDS 43.41, EC 43.62, Cl 21.1, Na 36.15, and in the RO membrane the salinity 72.02, TDS 60.26, EC 60.33, Cl 43.08, Na 54.41. Also in case of the rejection in hybrid system of those parameters and ions included salinity 78.65, TDS 76.52, EC 76.42, Cl 63.95, and Na 70.91. Comparing rejection percent in three above-mentioned methods, it could be concluded that, in reverse osmosis process, ions and non-ion parameters rejection ability were rather better than nanofiltration process, and also better in hybrid compared to reverse osmosis process. The results reported in this paper indicate that the integration of membrane nanofiltration with reverse osmosis (hybrid NF/RO) can be completed by each other probably to remove salinity, TDS, EC, Cl, and Na.

Hot Forging of a Cladded Component by Automated GMAW Process

NASA Astrophysics Data System (ADS)

Rafiq, Muhammad; Langlois, Laurent; Bigot, Régis

2011-01-01

Weld cladding is employed to improve the service life of engineering components by increasing corrosion and wear resistance and reducing the cost. The acceptable multi-bead cladding layer depends on single bead geometry. Hence, in first step, the relationship between input process parameters and the single bead geometry is studied and in second step a comprehensive study on multi bead clad layer deposition is carried out. This paper highlights an experimental study carried out to get single layer cladding deposited by automated Gas Metal Arc Welding (GMAW) process and to find the possibility of hot forming of the cladded work piece to get the final hot formed improved structure. GMAW is an arc welding process that uses an arc between a consumable electrode and the welding pool with an external shielding gas and the cladding is done by alongside deposition of weld beads. The experiments for single bead were conducted by varying the three main process parameters wire feed rate, arc voltage and welding speed while keeping other parameters like nozzle to work distance, shielding gas and its flow rate and torch angle constant. The effect of bead spacing and torch orientation on the cladding quality of single layer from the results of single bead deposition was studied. Effect of the dilution rate and nominal energy on the cladded layer hot bending quality was also performed at different temperatures.

Study on processing parameters of glass cutting by nanosecond 532 nm fiber laser

NASA Astrophysics Data System (ADS)

Wang, Jin; Gao, Fan; Xiong, Baoxing; Zhang, Xiang; Yuan, Xiao

2018-03-01

The processing parameters of soda-lime glass cutting with several nanosecond 532 nm pulsed fiber laser are studied in order to obtain sufficiently large ablation rate and better processing quality. The influences of laser processing parameters on effective cutting speed and cutting quality of 1 2 mm thick soda-lime glass are studied. The experimental results show that larger laser pulse energy will lead to higher effective cutting speed and larger maximum edge collapse of the front side of the glass samples. Compared with that of 1.1 mm thick glass samples, the 2.0 mm thick glass samples is more difficult to cut. With the pulse energy of 51.2 μJ, the maximum edge collapse is more than 200 μm for the 2.0 mm thick glass samples. In order to achieve the high effective cutting speed and good cutting quality at the same time, the dual energy overlapping method is used to obtain the better cutting performance for the 2.0 mm thick glass samples, and the cutting speed of 194 mm/s and the maximum edge collapse of less than 132 μm are realized.

Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone.

PubMed

Tahmasbi, Vahid; Ghoreishi, Majid; Zolfaghari, Mojtaba

2017-11-01

The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the aforementioned parameters. This optimization yielded a set of data that can considerably improve orthopedic osteosynthesis outcomes.

Integrated Process Modeling-A Process Validation Life Cycle Companion.

PubMed

Zahel, Thomas; Hauer, Stefan; Mueller, Eric M; Murphy, Patrick; Abad, Sandra; Vasilieva, Elena; Maurer, Daniel; Brocard, Cécile; Reinisch, Daniela; Sagmeister, Patrick; Herwig, Christoph

2017-10-17

During the regulatory requested process validation of pharmaceutical manufacturing processes, companies aim to identify, control, and continuously monitor process variation and its impact on critical quality attributes (CQAs) of the final product. It is difficult to directly connect the impact of single process parameters (PPs) to final product CQAs, especially in biopharmaceutical process development and production, where multiple unit operations are stacked together and interact with each other. Therefore, we want to present the application of Monte Carlo (MC) simulation using an integrated process model (IPM) that enables estimation of process capability even in early stages of process validation. Once the IPM is established, its capability in risk and criticality assessment is furthermore demonstrated. IPMs can be used to enable holistic production control strategies that take interactions of process parameters of multiple unit operations into account. Moreover, IPMs can be trained with development data, refined with qualification runs, and maintained with routine manufacturing data which underlines the lifecycle concept. These applications will be shown by means of a process characterization study recently conducted at a world-leading contract manufacturing organization (CMO). The new IPM methodology therefore allows anticipation of out of specification (OOS) events, identify critical process parameters, and take risk-based decisions on counteractions that increase process robustness and decrease the likelihood of OOS events.

Parametric Study and Multi-Criteria Optimization in Laser Cladding by a High Power Direct Diode Laser

NASA Astrophysics Data System (ADS)

Farahmand, Parisa; Kovacevic, Radovan

2014-12-01

In laser cladding, the performance of the deposited layers subjected to severe working conditions (e.g., wear and high temperature conditions) depends on the mechanical properties, the metallurgical bond to the substrate, and the percentage of dilution. The clad geometry and mechanical characteristics of the deposited layer are influenced greatly by the type of laser used as a heat source and process parameters used. Nowadays, the quality of fabricated coating by laser cladding and the efficiency of this process has improved thanks to the development of high-power diode lasers, with power up to 10 kW. In this study, the laser cladding by a high power direct diode laser (HPDDL) as a new heat source in laser cladding was investigated in detail. The high alloy tool steel material (AISI H13) as feedstock was deposited on mild steel (ASTM A36) by a HPDDL up to 8kW laser and with new design lateral feeding nozzle. The influences of the main process parameters (laser power, powder flow rate, and scanning speed) on the clad-bead geometry (specifically layer height and depth of the heat affected zone), and clad microhardness were studied. Multiple regression analysis was used to develop the analytical models for desired output properties according to input process parameters. The Analysis of Variance was applied to check the accuracy of the developed models. The response surface methodology (RSM) and desirability function were used for multi-criteria optimization of the cladding process. In order to investigate the effect of process parameters on the molten pool evolution, in-situ monitoring was utilized. Finally, the validation results for optimized process conditions show the predicted results were in a good agreement with measured values. The multi-criteria optimization makes it possible to acquire an efficient process for a combination of clad geometrical and mechanical characteristics control.

Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach

NASA Astrophysics Data System (ADS)

Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.

2016-09-01

The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.

Overview of Icing Physics Relevant to Scaling

NASA Technical Reports Server (NTRS)

Anderson, David N.; Tsao, Jen-Ching

2005-01-01

An understanding of icing physics is required for the development of both scaling methods and ice-accretion prediction codes. This paper gives an overview of our present understanding of the important physical processes and the associated similarity parameters that determine the shape of Appendix C ice accretions. For many years it has been recognized that ice accretion processes depend on flow effects over the model, on droplet trajectories, on the rate of water collection and time of exposure, and, for glaze ice, on a heat balance. For scaling applications, equations describing these events have been based on analyses at the stagnation line of the model and have resulted in the identification of several non-dimensional similarity parameters. The parameters include the modified inertia parameter of the water drop, the accumulation parameter and the freezing fraction. Other parameters dealing with the leading edge heat balance have also been used for convenience. By equating scale expressions for these parameters to the values to be simulated a set of equations is produced which can be solved for the scale test conditions. Studies in the past few years have shown that at least one parameter in addition to those mentioned above is needed to describe surface-water effects, and some of the traditional parameters may not be as significant as once thought. Insight into the importance of each parameter, and the physical processes it represents, can be made by viewing whether ice shapes change, and the extent of the change, when each parameter is varied. Experimental evidence is presented to establish the importance of each of the traditionally used parameters and to identify the possible form of a new similarity parameter to be used for scaling.

Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.

2016-12-01

This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for improving the model physics parameterizations.

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Laser Peening Process and Its Impact on Materials Properties in Comparison with Shot Peening and Ultrasonic Impact Peening

PubMed Central

Gujba, Abdullahi K.; Medraj, Mamoun

2014-01-01

The laser shock peening (LSP) process using a Q-switched pulsed laser beam for surface modification has been reviewed. The development of the LSP technique and its numerous advantages over the conventional shot peening (SP) such as better surface finish, higher depths of residual stress and uniform distribution of intensity were discussed. Similar comparison with ultrasonic impact peening (UIP)/ultrasonic shot peening (USP) was incorporated, when possible. The generation of shock waves, processing parameters, and characterization of LSP treated specimens were described. Special attention was given to the influence of LSP process parameters on residual stress profiles, material properties and structures. Based on the studies so far, more fundamental understanding is still needed when selecting optimized LSP processing parameters and substrate conditions. A summary of the parametric studies of LSP on different materials has been presented. Furthermore, enhancements in the surface micro and nanohardness, elastic modulus, tensile yield strength and refinement of microstructure which translates to increased fatigue life, fretting fatigue life, stress corrosion cracking (SCC) and corrosion resistance were addressed. However, research gaps related to the inconsistencies in the literature were identified. Current status, developments and challenges of the LSP technique were discussed. PMID:28788284

Modeling of microstructure evolution in direct metal laser sintering: A phase field approach

NASA Astrophysics Data System (ADS)

Nandy, Jyotirmoy; Sarangi, Hrushikesh; Sahoo, Seshadev

2017-02-01

Direct Metal Laser Sintering (DMLS) is a new technology in the field of additive manufacturing, which builds metal parts in a layer by layer fashion directly from the powder bed. The process occurs within a very short time period with rapid solidification rate. Slight variations in the process parameters may cause enormous change in the final build parts. The physical and mechanical properties of the final build parts are dependent on the solidification rate which directly affects the microstructure of the material. Thus, the evolving of microstructure plays a vital role in the process parameters optimization. Nowadays, the increase in computational power allows for direct simulations of microstructures during materials processing for specific manufacturing conditions. In this study, modeling of microstructure evolution of Al-Si-10Mg powder in DMLS process was carried out by using a phase field approach. A MATLAB code was developed to solve the set of phase field equations, where simulation parameters include temperature gradient, laser scan speed and laser power. The effects of temperature gradient on microstructure evolution were studied and found that with increase in temperature gradient, the dendritic tip grows at a faster rate.

Parameters in selective laser melting for processing metallic powders

NASA Astrophysics Data System (ADS)

Kurzynowski, Tomasz; Chlebus, Edward; Kuźnicka, Bogumiła; Reiner, Jacek

2012-03-01

The paper presents results of studies on Selective Laser Melting. SLM is an additive manufacturing technology which may be used to process almost all metallic materials in the form of powder. Types of energy emission sources, mainly fiber lasers and/or Nd:YAG laser with similar characteristics and the wavelength of 1,06 - 1,08 microns, are provided primarily for processing metallic powder materials with high absorption of laser radiation. The paper presents results of selected variable parameters (laser power, scanning time, scanning strategy) and fixed parameters such as the protective atmosphere (argon, nitrogen, helium), temperature, type and shape of the powder material. The thematic scope is very broad, so the work was focused on optimizing the process of selective laser micrometallurgy for producing fully dense parts. The density is closely linked with other two conditions: discontinuity of the microstructure (microcracks) and stability (repeatability) of the process. Materials used for the research were stainless steel 316L (AISI), tool steel H13 (AISI), and titanium alloy Ti6Al7Nb (ISO 5832-11). Studies were performed with a scanning electron microscope, a light microscopes, a confocal microscope and a μCT scanner.

Simulation and analysis of tape spring for deployed space structures

NASA Astrophysics Data System (ADS)

Chang, Wei; Cao, DongJing; Lian, MinLong

2018-03-01

The tape spring belongs to the configuration of ringent cylinder shell, and the mechanical properties of the structure are significantly affected by the change of geometrical parameters. There are few studies on the influence of geometrical parameters on the mechanical properties of the tape spring. The bending process of the single tape spring was simulated based on simulation software. The variations of critical moment, unfolding moment, and maximum strain energy in the bending process were investigated, and the effects of different radius angles of section and thickness and length on driving capability of the simple tape spring was studied by using these parameters. Results show that the driving capability and resisting disturbance capacity grow with the increase of radius angle of section in the bending process of the single tape spring. On the other hand, these capabilities decrease with increasing length of the single tape spring. In the end, the driving capability and resisting disturbance capacity grow with the increase of thickness in the bending process of the single tape spring. The research has a certain reference value for improving the kinematic accuracy and reliability of deployable structures.

Analyzing the Effect of Spinning Process Variables on Draw Frame Blended Cotton Mélange Yarn Quality

NASA Astrophysics Data System (ADS)

Ray, Suchibrata; Ghosh, Anindya; Banerjee, Debamalya

2018-06-01

An investigation has been made to study the effect of important spinning process variables namely shade depth, ring frame spindle speed and yarn twist multiplier (TM) on various yarn quality parameters like unevenness, strength, imperfection, elongation at break and hairiness index of draw frame blended cotton mélange yarn. Three factors Box and Behnken design of experiment has been used to conduct the study. The quadratic regression model is used to device the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Analysis of the results show that yarn strength of draw frame blended cotton mélange yarn is significantly affected by shade depth and TM. Yarn unevenness is affected by shade depth and ring frame spindle speed. Yarn imperfection level is mainly influenced by the shade depth and spindle speed. The shade depth and yarn TM have shown significant impact on yarn hairiness index.

Analyzing the Effect of Spinning Process Variables on Draw Frame Blended Cotton Mélange Yarn Quality

NASA Astrophysics Data System (ADS)

Ray, Suchibrata; Ghosh, Anindya; Banerjee, Debamalya

2017-12-01

An investigation has been made to study the effect of important spinning process variables namely shade depth, ring frame spindle speed and yarn twist multiplier (TM) on various yarn quality parameters like unevenness, strength, imperfection, elongation at break and hairiness index of draw frame blended cotton mélange yarn. Three factors Box and Behnken design of experiment has been used to conduct the study. The quadratic regression model is used to device the statistical inferences about sensitivity of the yarn quality parameters to the different process variables. The response surfaces are constructed for depicting the geometric representation of yarn quality parameters plotted as a function of process variables. Analysis of the results show that yarn strength of draw frame blended cotton mélange yarn is significantly affected by shade depth and TM. Yarn unevenness is affected by shade depth and ring frame spindle speed. Yarn imperfection level is mainly influenced by the shade depth and spindle speed. The shade depth and yarn TM have shown significant impact on yarn hairiness index.

Sensitivity analysis of coupled processes and parameters on the performance of enhanced geothermal systems.

PubMed

Pandey, S N; Vishal, Vikram

2017-12-06

3-D modeling of coupled thermo-hydro-mechanical (THM) processes in enhanced geothermal systems using the control volume finite element code was done. In a first, a comparative analysis on the effects of coupled processes, operational parameters and reservoir parameters on heat extraction was conducted. We found that significant temperature drop and fluid overpressure occurred inside the reservoirs/fracture that affected the transport behavior of the fracture. The spatio-temporal variations of fracture aperture greatly impacted the thermal drawdown and consequently the net energy output. The results showed that maximum aperture evolution occurred near the injection zone instead of the production zone. Opening of the fracture reduced the injection pressure required to circulate a fixed mass of water. The thermal breakthrough and heat extraction strongly depend on the injection mass flow rate, well distances, reservoir permeability and geothermal gradients. High permeability caused higher water loss, leading to reduced heat extraction. From the results of TH vs THM process simulations, we conclude that appropriate coupling is vital and can impact the estimates of net heat extraction. This study can help in identifying the critical operational parameters, and process optimization for enhanced energy extraction from a geothermal system.

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

NASA Astrophysics Data System (ADS)

Kelleher, Christa; McGlynn, Brian; Wagener, Thorsten

2017-07-01

Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

PubMed

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

Fatigue behavior of thermal sprayed WC-CoCr- steel systems: Role of process and deposition parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vackel, Andrew; Sampath, Sanjay

Thermal spray deposited WC-CoCr coatings are extensively used for surface protection of wear prone components in a variety of applications. Although the primary purpose of the coating is wear and corrosion protection, many of the coated components are structural systems (aero landing gear, hydraulic cylinders, drive shafts etc.) and as such experience cyclic loading during service and are potentially prone to fatigue failure. It is of interest to ensure that the coating and the application process does not deleteriously affect the fatigue strength of the parent structural metal. It has long been appreciated that the relative fatigue life of amore » thermal sprayed component can be affected by the residual stresses arising from coating deposition. The magnitude of these stresses can be managed by torch processing parameters and can also be influenced by deposition effects, particularly the deposition temperature. In this study, the effect of both torch operating parameters (particle states) and deposition conditions (notably substrate temperature) were investigated through rotating bending fatigue studies. The results indicate a strong influence of process parameters on relative fatigue life, including credit or debit to the substrate's fatigue life measured via rotating bend beam studies. Damage progression within the substrate was further explored by stripping the coating off part way through fatigue testing, revealing a delay in the onset of substrate damage with more fatigue resistant coatings but no benefit with coatings with inadequate properties. Finally, the results indicate that compressive residual stress and adequate load bearing capability of the coating (both controlled by torch and deposition parameters) delay onset of substrate damage, enabling fatigue credit of the coated component.« less

Fatigue behavior of thermal sprayed WC-CoCr- steel systems: Role of process and deposition parameters

DOE PAGES

Vackel, Andrew; Sampath, Sanjay

2017-02-27

Thermal spray deposited WC-CoCr coatings are extensively used for surface protection of wear prone components in a variety of applications. Although the primary purpose of the coating is wear and corrosion protection, many of the coated components are structural systems (aero landing gear, hydraulic cylinders, drive shafts etc.) and as such experience cyclic loading during service and are potentially prone to fatigue failure. It is of interest to ensure that the coating and the application process does not deleteriously affect the fatigue strength of the parent structural metal. It has long been appreciated that the relative fatigue life of amore » thermal sprayed component can be affected by the residual stresses arising from coating deposition. The magnitude of these stresses can be managed by torch processing parameters and can also be influenced by deposition effects, particularly the deposition temperature. In this study, the effect of both torch operating parameters (particle states) and deposition conditions (notably substrate temperature) were investigated through rotating bending fatigue studies. The results indicate a strong influence of process parameters on relative fatigue life, including credit or debit to the substrate's fatigue life measured via rotating bend beam studies. Damage progression within the substrate was further explored by stripping the coating off part way through fatigue testing, revealing a delay in the onset of substrate damage with more fatigue resistant coatings but no benefit with coatings with inadequate properties. Finally, the results indicate that compressive residual stress and adequate load bearing capability of the coating (both controlled by torch and deposition parameters) delay onset of substrate damage, enabling fatigue credit of the coated component.« less

Process to evaluate hematological parameters that reflex to manual differential cell counts in a pediatric institution.

PubMed

Guarner, Jeannette; Atuan, Maria Ana; Nix, Barbara; Mishak, Christopher; Vejjajiva, Connie; Curtis, Cheri; Park, Sunita; Mullins, Richard

2010-01-01

Each institution sets specific parameters obtained by automated hematology analyzers to trigger manual counts. We designed a process to decrease the number of manual differential cell counts without impacting patient care. We selected new criteria that prompt manual counts and studied the impact these changes had in 2 days of work and in samples of patients with newly diagnosed leukemia, sickle cell disease, and presence of left shift. By using fewer parameters and expanding our ranges we decreased the number of manual counts by 20%. The parameters that prompted manual counts most frequently were the presence of blast flags and nucleated red blood cells, 2 parameters that were not changed. The parameters that accounted for a decrease in the number of manual counts were the white blood cell count and large unstained cells. Eight of 32 patients with newly diagnosed leukemia did not show blast flags; however, other parameters triggered manual counts. In 47 patients with sickle cell disease, nucleated red cells and red cell variability prompted manual review. Bands were observed in 18% of the specimens and 4% would not have been counted manually with the new criteria, for the latter the mean band count was 2.6%. The process we followed to evaluate hematological parameters that reflex to manual differential cell counts increased efficiency without compromising patient care in our hospital system.

Disentangling inhibition-based and retrieval-based aftereffects of distractors: Cognitive versus motor processes.

PubMed

Singh, Tarini; Laub, Ruth; Burgard, Jan Pablo; Frings, Christian

2018-05-01

Selective attention refers to the ability to selectively act upon relevant information at the expense of irrelevant information. Yet, in many experimental tasks, what happens to the representation of the irrelevant information is still debated. Typically, 2 approaches to distractor processing have been suggested, namely distractor inhibition and distractor-based retrieval. However, it is also typical that both processes are hard to disentangle. For instance, in the negative priming literature (for a review Frings, Schneider, & Fox, 2015) this has been a continuous debate since the early 1980s. In the present study, we attempted to prove that both processes exist, but that they reflect distractor processing at different levels of representation. Distractor inhibition impacts stimulus representation, whereas distractor-based retrieval impacts mainly motor processes. We investigated both processes in a distractor-priming task, which enables an independent measurement of both processes. For our argument that both processes impact different levels of distractor representation, we estimated the exponential parameter (τ) and Gaussian components (μ, σ) of the exponential Gaussian reaction-time (RT) distribution, which have previously been used to independently test the effects of cognitive and motor processes (e.g., Moutsopoulou & Waszak, 2012). The distractor-based retrieval effect was evident for the Gaussian component, which is typically discussed as reflecting motor processes, but not for the exponential parameter, whereas the inhibition component was evident for the exponential parameter, which is typically discussed as reflecting cognitive processes, but not for the Gaussian parameter. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Geometry characteristics modeling and process optimization in coaxial laser inside wire cladding

NASA Astrophysics Data System (ADS)

Shi, Jianjun; Zhu, Ping; Fu, Geyan; Shi, Shihong

2018-05-01

Coaxial laser inside wire cladding method is very promising as it has a very high efficiency and a consistent interaction between the laser and wire. In this paper, the energy and mass conservation law, and the regression algorithm are used together for establishing the mathematical models to study the relationship between the layer geometry characteristics (width, height and cross section area) and process parameters (laser power, scanning velocity and wire feeding speed). At the selected parameter ranges, the predicted values from the models are compared with the experimental measured results, and there is minor error existing, but they reflect the same regularity. From the models, it is seen the width of the cladding layer is proportional to both the laser power and wire feeding speed, while it firstly increases and then decreases with the increasing of the scanning velocity. The height of the cladding layer is proportional to the scanning velocity and feeding speed and inversely proportional to the laser power. The cross section area increases with the increasing of feeding speed and decreasing of scanning velocity. By using the mathematical models, the geometry characteristics of the cladding layer can be predicted by the known process parameters. Conversely, the process parameters can be calculated by the targeted geometry characteristics. The models are also suitable for multi-layer forming process. By using the optimized process parameters calculated from the models, a 45 mm-high thin-wall part is formed with smooth side surfaces.

Period Estimation for Sparsely-sampled Quasi-periodic Light Curves Applied to Miras

NASA Astrophysics Data System (ADS)

He, Shiyuan; Yuan, Wenlong; Huang, Jianhua Z.; Long, James; Macri, Lucas M.

2016-12-01

We develop a nonlinear semi-parametric Gaussian process model to estimate periods of Miras with sparsely sampled light curves. The model uses a sinusoidal basis for the periodic variation and a Gaussian process for the stochastic changes. We use maximum likelihood to estimate the period and the parameters of the Gaussian process, while integrating out the effects of other nuisance parameters in the model with respect to a suitable prior distribution obtained from earlier studies. Since the likelihood is highly multimodal for period, we implement a hybrid method that applies the quasi-Newton algorithm for Gaussian process parameters and search the period/frequency parameter space over a dense grid. A large-scale, high-fidelity simulation is conducted to mimic the sampling quality of Mira light curves obtained by the M33 Synoptic Stellar Survey. The simulated data set is publicly available and can serve as a testbed for future evaluation of different period estimation methods. The semi-parametric model outperforms an existing algorithm on this simulated test data set as measured by period recovery rate and quality of the resulting period-luminosity relations.

Multi Objective Optimization of Multi Wall Carbon Nanotube Based Nanogrinding Wheel Using Grey Relational and Regression Analysis

NASA Astrophysics Data System (ADS)

Sethuramalingam, Prabhu; Vinayagam, Babu Kupusamy

2016-07-01

Carbon nanotube mixed grinding wheel is used in the grinding process to analyze the surface characteristics of AISI D2 tool steel material. Till now no work has been carried out using carbon nanotube based grinding wheel. Carbon nanotube based grinding wheel has excellent thermal conductivity and good mechanical properties which are used to improve the surface finish of the workpiece. In the present study, the multi response optimization of process parameters like surface roughness and metal removal rate of grinding process of single wall carbon nanotube (CNT) in mixed cutting fluids is undertaken using orthogonal array with grey relational analysis. Experiments are performed with designated grinding conditions obtained using the L9 orthogonal array. Based on the results of the grey relational analysis, a set of optimum grinding parameters is obtained. Using the analysis of variance approach the significant machining parameters are found. Empirical model for the prediction of output parameters has been developed using regression analysis and the results are compared empirically, for conditions of with and without CNT grinding wheel in grinding process.

Radiation Pressure Cooling as a Quantum Dynamical Process

NASA Astrophysics Data System (ADS)

He, Bing; Yang, Liu; Lin, Qing; Xiao, Min

2017-06-01

One of the most fundamental problems in optomechanical cooling is how small the thermal phonon number of a mechanical oscillator can be achieved under the radiation pressure of a proper cavity field. Different from previous theoretical predictions, which were based on an optomechanical system's time-independent steady states, we treat such cooling as a dynamical process of driving the mechanical oscillator from its initial thermal state, due to its thermal equilibrium with the environment, to a stabilized quantum state of higher purity. We find that the stabilized thermal phonon number left in the end actually depends on how fast the cooling process could be. The cooling speed is decided by an effective optomechanical coupling intensity, which constitutes an essential parameter for cooling, in addition to the sideband resolution parameter that has been considered in other theoretical studies. The limiting thermal phonon number that any cooling process cannot surpass exhibits a discontinuous jump across a certain value of the parameter.

Examining Mechanical Strength Characteristics of Selective Inhibition Sintered HDPE Specimens Using RSM and Desirability Approach

NASA Astrophysics Data System (ADS)

Rajamani, D.; Esakki, Balasubramanian

2017-09-01

Selective inhibition sintering (SIS) is a powder based additive manufacturing (AM) technique to produce functional parts with an inexpensive system compared with other AM processes. Mechanical properties of SIS fabricated parts are of high dependence on various process parameters importantly layer thickness, heat energy, heater feedrate, and printer feedrate. In this paper, examining the influence of these process parameters on evaluating mechanical properties such as tensile and flexural strength using Response Surface Methodology (RSM) is carried out. The test specimens are fabricated using high density polyethylene (HDPE) and mathematical models are developed to correlate the control factors to the respective experimental design response. Further, optimal SIS process parameters are determined using desirability approach to enhance the mechanical properties of HDPE specimens. Optimization studies reveal that, combination of high heat energy, low layer thickness, medium heater feedrate and printer feedrate yielded superior mechanical strength characteristics.

V2S: Voice to Sign Language Translation System for Malaysian Deaf People

NASA Astrophysics Data System (ADS)

Mean Foong, Oi; Low, Tang Jung; La, Wai Wan

The process of learning and understand the sign language may be cumbersome to some, and therefore, this paper proposes a solution to this problem by providing a voice (English Language) to sign language translation system using Speech and Image processing technique. Speech processing which includes Speech Recognition is the study of recognizing the words being spoken, regardless of whom the speaker is. This project uses template-based recognition as the main approach in which the V2S system first needs to be trained with speech pattern based on some generic spectral parameter set. These spectral parameter set will then be stored as template in a database. The system will perform the recognition process through matching the parameter set of the input speech with the stored templates to finally display the sign language in video format. Empirical results show that the system has 80.3% recognition rate.

Optimization of methylene blue using Ca(2+) and Zn(2+) bio-polymer hydrogel beads: A comparative study.

PubMed

Kumar, M; Tamilarasan, R; Arthanareeswaran, G; Ismail, A F

2015-11-01

Recently noted that the methylene blue cause severe central nervous system toxicity. It is essential to optimize the methylene blue from aqueous environment. In this study, a comparison of an optimization of methylene blue was investigated by using modified Ca(2+) and Zn(2+) bio-polymer hydrogel beads. A batch mode study was conducted using various parameters like time, dye concentration, bio-polymer dose, pH and process temperature. The isotherms, kinetics, diffusion and thermodynamic studies were performed for feasibility of the optimization process. Freundlich and Langmuir isotherm equations were used for the prediction of isotherm parameters and correlated with dimensionless separation factor (RL). Pseudo-first order and pseudo-second order Lagegren's kinetic equations were used for the correlation of kinetic parameters. Intraparticle diffusion model was employed for diffusion of the optimization process. The Fourier Transform Infrared Spectroscopy (FTIR) shows different absorbent peaks of Ca(2+) and Zn(2+) beads and the morphology of the bio-polymer material analyzed with Scanning Electron Microscope (SEM). The TG & DTA studies show that good thermal stability with less humidity without production of any non-degraded products. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling spray/puddle dissolution processes for deep-ultraviolet acid-hardened resists

NASA Astrophysics Data System (ADS)

Hutchinson, John M.; Das, Siddhartha; Qian, Qi-De; Gaw, Henry T.

1993-10-01

A study of the dissolution behavior of acid-hardened resists (AHR) was undertaken for spray and spray/puddle development processes. The Site Services DSM-100 end-point detection system is used to measure both spray and puddle dissolution data for a commercially available deep-ultraviolet AHR resist, Shipley SNR-248. The DSM allows in situ measurement of dissolution rate on the wafer chuck and hence allows parameter extraction for modeling spray and puddle processes. The dissolution data for spray and puddle processes was collected across a range of exposure dose and postexposure bake temperature. The development recipe was varied to decouple the contribution of the spray and puddle modes to the overall dissolution characteristics. The mechanisms involved in spray versus puddle dissolution and the impact of spray versus puddle dissolution on process performance metrics has been investigated. We used the effective-dose-modeling approach and the measurement capability of the DSM-100 and developed a lumped parameter model for acid-hardened resists that incorporates the effects of exposure, postexposure bake temperature and time, and development condition. The PARMEX photoresist-modeling program is used to determine parameters for the spray and for the puddle process. The lumped parameter AHR model developed showed good agreement with experimental data.

[Studies on the process of Herba Clinopodii saponins purified with macroporous adsorption resin].

PubMed

Zhang, Yi; Yan, Dan; Han, Yumei

2005-10-01

To study the technological parameters of the purification process of saponins with macroporous adsorption resin. The adsorptive characteristics and elutive parameters of the process were studied by taking the elutive and purified ratio of saponins as markers. 11.4 ml of the extraction of Herba Clinopodii (crude drugs 0.2 g/ml) was purified with a column of macroporous adsorption resin (phi15 mm x H90 mm, dry weight 2.5 g) and washed with 3BV of distilled water, then eluted with 3BV of 30% ethanol and 3BV of 70% ethanol. Most of saponins were collected in the 70% ethanol. With macroporous adsorption resin adsorbing and purifying,the elutive ratio of saponins is 86.8% and the purity reaches 153.2%. So this process of applying macroporous adsorption resin to adsorb and purify Saponins is feasible.

Selective attention and the "Asynchrony Theory" in native Hebrew-speaking adult dyslexics: Behavioral and ERPs measures.

PubMed

Menashe, Shay

2017-01-01

The main aim of the present study was to determine whether adult dyslexic readers demonstrate the "Asynchrony Theory" (Breznitz [Reading Fluency: Synchronization of Processes, Lawrence Erlbaum and Associates, Mahwah, NJ, USA, 2006]) when selective attention is studied. Event-related potentials (ERPs) and behavioral parameters were collected from nonimpaired readers group and dyslexic readers group performing alphabetic and nonalphabetic tasks. The dyslexic readers group was found to demonstrate asynchrony between the auditory and the visual modalities when it came to processing alphabetic stimuli. These findings were found both for behavioral and ERPs parameters. Unlike the dyslexic readers, the nonimpaired readers showed synchronized speed of processing in the auditory and the visual modalities while processing alphabetic stimuli. The current study suggests that established reading is dependent on a synchronization between the auditory and the visual modalities even when it comes to selective attention.

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in adequately representing the relevant process to capture limiting resources or manage atypical environmental conditions. These results may inform future experimental work by focusing efforts on quantifying specific parameters under various environmental conditions or across diverse plant functional types.

Fabrication of amplitude-phase type diffractive optical elements in aluminium films

NASA Astrophysics Data System (ADS)

Fomchenkov, S. A.; Butt, M. A.

2017-11-01

In the course of studies have been conducted a method of forming the phase diffractive optical elements (DOEs) by direct laser writing in thin films of aluminum. The quality of the aluminum films were investigated depending on the parameters of magnetron sputtering process. Moreover, the parameters of the laser writing process in thin films of aluminum were optimized. The structure of phase diffractive optical elements was obtained by the proposed method.

Optimizing pulsed Nd:YAG laser beam welding process parameters to attain maximum ultimate tensile strength for thin AISI316L sheet using response surface methodology and simulated annealing algorithm

NASA Astrophysics Data System (ADS)

Torabi, Amir; Kolahan, Farhad

2018-07-01

Pulsed laser welding is a powerful technique especially suitable for joining thin sheet metals. In this study, based on experimental data, pulsed laser welding of thin AISI316L austenitic stainless steel sheet has been modeled and optimized. The experimental data required for modeling are gathered as per Central Composite Design matrix in Response Surface Methodology (RSM) with full replication of 31 runs. Ultimate Tensile Strength (UTS) is considered as the main quality measure in laser welding. Furthermore, the important process parameters including peak power, pulse duration, pulse frequency and welding speed are selected as input process parameters. The relation between input parameters and the output response is established via full quadratic response surface regression with confidence level of 95%. The adequacy of the regression model was verified using Analysis of Variance technique results. The main effects of each factor and the interactions effects with other factors were analyzed graphically in contour and surface plot. Next, to maximum joint UTS, the best combinations of parameters levels were specified using RSM. Moreover, the mathematical model is implanted into a Simulated Annealing (SA) optimization algorithm to determine the optimal values of process parameters. The results obtained by both SA and RSM optimization techniques are in good agreement. The optimal parameters settings for peak power of 1800 W, pulse duration of 4.5 ms, frequency of 4.2 Hz and welding speed of 0.5 mm/s would result in a welded joint with 96% of the base metal UTS. Computational results clearly demonstrate that the proposed modeling and optimization procedures perform quite well for pulsed laser welding process.

Ring rolling process simulation for geometry optimization

NASA Astrophysics Data System (ADS)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Ring Rolling is a complex hot forming process where different rolls are involved in the production of seamless rings. Since each roll must be independently controlled, different speed laws must be set; usually, in the industrial environment, a milling curve is introduced to monitor the shape of the workpiece during the deformation in order to ensure the correct ring production. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular speed of main roll) on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR (Hot Ring Rolling) has been implemented in SFTC DEFORM V11. The FEM model has been used to formulate a proper optimization problem. The optimization procedure has been implemented in the commercial software DS ISight in order to find the combination of process parameters which allows to minimize the percentage error of each obtained dimension with respect to its nominal value. The software allows to find the relationship between input and output parameters applying Response Surface Methodology (RSM), by using the exact values of output parameters in the control points of the design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. After the calculation of the response surfaces for the selected output parameters, an optimization procedure based on Genetic Algorithms has been applied. At the end, the error between each obtained dimension and its nominal value has been minimized. The constraints imposed were the maximum values of standard deviations of the dimensions obtained for the final ring.

Laser Processing of Multilayered Thermal Spray Coatings: Optimal Processing Parameters

NASA Astrophysics Data System (ADS)

Tewolde, Mahder; Zhang, Tao; Lee, Hwasoo; Sampath, Sanjay; Hwang, David; Longtin, Jon

2017-12-01

Laser processing offers an innovative approach for the fabrication and transformation of a wide range of materials. As a rapid, non-contact, and precision material removal technology, lasers are natural tools to process thermal spray coatings. Recently, a thermoelectric generator (TEG) was fabricated using thermal spray and laser processing. The TEG device represents a multilayer, multimaterial functional thermal spray structure, with laser processing serving an essential role in its fabrication. Several unique challenges are presented when processing such multilayer coatings, and the focus of this work is on the selection of laser processing parameters for optimal feature quality and device performance. A parametric study is carried out using three short-pulse lasers, where laser power, repetition rate and processing speed are varied to determine the laser parameters that result in high-quality features. The resulting laser patterns are characterized using optical and scanning electron microscopy, energy-dispersive x-ray spectroscopy, and electrical isolation tests between patterned regions. The underlying laser interaction and material removal mechanisms that affect the feature quality are discussed. Feature quality was found to improve both by using a multiscanning approach and an optional assist gas of air or nitrogen. Electrically isolated regions were also patterned in a cylindrical test specimen.

Integrating uncertainties to the combined environmental and economic assessment of algal biorefineries: A Monte Carlo approach.

PubMed

Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J

2018-06-01

The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.

Heat and water rate transfer processes in the human respiratory tract at various altitudes.

PubMed

Kandjov, I M

2001-02-01

The process of the respiratory air conditioning as a process of heat and mass exchange at the interface inspired air-airways surface was studied. Using a model of airways (Olson et al., 1970) where the segments of the respiratory tract are like cylinders with a fixed length and diameter, the corresponding heat transfer equations, in the paper are founded basic rate exchange parameters-convective heat transfer coefficient h(c)(W m(-2) degrees C(-1)) and evaporative heat transfer coefficient h(e)(W m(-2)hPa(-1)). The rate transfer parameters assumed as sources with known heat power are connected to airflow rate in different airways segments. Relationships expressing warming rate of inspired air due to convection, warming rate of inspired air due to evaporation, water diffused in the inspired air from the airways wall, i.e. a system of air conditioning parameters, was composed. The altitude dynamics of the relations is studied. Every rate conditioning parameter is an increasing function of altitude. The process of diffusion in the peripheral bronchial generations as a basic transfer process is analysed. The following phenomenon is in effect: the diffusion coefficient increases with altitude and causes a compensation of simultaneous decreasing of O(2)and CO(2)densities in atmospheric air. Due to this compensation, the diffusion in the peripheral generations with altitude is approximately constant. The elements of the human anatomy optimality as well as the established dynamics are discussed and assumed. The square form of the airways after the trachea expressed in terms of transfer supposes (in view of maximum contact surface), that a maximum heat and water exchange is achieved, i.e. high degree of air condition at fixed environmental parameters and respiration regime. Copyright 2001 Academic Press.

A Comparative Study on Ni-Based Coatings Prepared by HVAF, HVOF, and APS Methods for Corrosion Protection Applications

NASA Astrophysics Data System (ADS)

Sadeghimeresht, E.; Markocsan, N.; Nylén, P.

2016-12-01

Selection of the thermal spray process is the most important step toward a proper coating solution for a given application as important coating characteristics such as adhesion and microstructure are highly dependent on it. In the present work, a process-microstructure-properties-performance correlation study was performed in order to figure out the main characteristics and corrosion performance of the coatings produced by different thermal spray techniques such as high-velocity air fuel (HVAF), high-velocity oxy fuel (HVOF), and atmospheric plasma spraying (APS). Previously optimized HVOF and APS process parameters were used to deposit Ni, NiCr, and NiAl coatings and compare with HVAF-sprayed coatings with randomly selected process parameters. As the HVAF process presented the best coating characteristics and corrosion behavior, few process parameters such as feed rate and standoff distance (SoD) were investigated to systematically optimize the HVAF coatings in terms of low porosity and high corrosion resistance. The Ni and NiAl coatings with lower porosity and better corrosion behavior were obtained at an average SoD of 300 mm and feed rate of 150 g/min. The NiCr coating sprayed at a SoD of 250 mm and feed rate of 75 g/min showed the highest corrosion resistance among all investigated samples.

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Influence of the "surface effect" on the segregation parameters of S in Fe(100): A multi-scale modelling and Auger Electron Spectroscopy study

NASA Astrophysics Data System (ADS)

Barnard, P. E.; Terblans, J. J.; Swart, H. C.

2015-12-01

The article takes a new look at the process of atomic segregation by considering the influence of surface relaxation on the segregation parameters; the activation energy (Q), segregation energy (ΔG), interaction parameter (Ω) and the pre-exponential factor (D0). Computational modelling, namely Density Functional Theory (DFT) and the Modified Darken Model (MDM) in conjunction with Auger Electron Spectroscopy (AES) was utilized to study the variation of the segregation parameters for S in the surface region of Fe(100). Results indicate a variation in each of the segregation parameters as a function of the atomic layer under consideration. Values of the segregation parameters varied more dramatically as the surface layer is approached, with atomic layer 2 having the largest deviations in comparison to the bulk values. This atomic layer had the highest Q value and formed the rate limiting step for the segregation of S towards the Fe(100) surface. It was found that the segregation process is influenced by two sets of segregation parameters, those of the surface region formed by atomic layer 2, and those in the bulk material. This article is the first to conduct a full scale investigation on the influence of surface relaxation on segregation and labelled it the "surface effect".

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Influence of Layer Thickness, Raster Angle, Deformation Temperature and Recovery Temperature on the Shape-Memory Effect of 3D-Printed Polylactic Acid Samples

PubMed Central

Wu, Wenzheng; Ye, Wenli; Wu, Zichao; Geng, Peng; Wang, Yulei; Zhao, Ji

2017-01-01

The success of the 3D-printing process depends upon the proper selection of process parameters. However, the majority of current related studies focus on the influence of process parameters on the mechanical properties of the parts. The influence of process parameters on the shape-memory effect has been little studied. This study used the orthogonal experimental design method to evaluate the influence of the layer thickness H, raster angle θ, deformation temperature Td and recovery temperature Tr on the shape-recovery ratio Rr and maximum shape-recovery rate Vm of 3D-printed polylactic acid (PLA). The order and contribution of every experimental factor on the target index were determined by range analysis and ANOVA, respectively. The experimental results indicated that the recovery temperature exerted the greatest effect with a variance ratio of 416.10, whereas the layer thickness exerted the smallest effect on the shape-recovery ratio with a variance ratio of 4.902. The recovery temperature exerted the most significant effect on the maximum shape-recovery rate with the highest variance ratio of 1049.50, whereas the raster angle exerted the minimum effect with a variance ratio of 27.163. The results showed that the shape-memory effect of 3D-printed PLA parts depended strongly on recovery temperature, and depended more weakly on the deformation temperature and 3D-printing parameters. PMID:28825617

Statistical analysis and optimization of direct metal laser deposition of 227-F Colmonoy nickel alloy

NASA Astrophysics Data System (ADS)

Angelastro, A.; Campanelli, S. L.; Casalino, G.

2017-09-01

This paper presents a study on process parameters and building strategy for the deposition of Colmonoy 227-F powder by CO2 laser with a focal spot diameter of 0.3 mm. Colmonoy 227-F is a nickel alloy especially designed for mold manufacturing. The substrate material is a 10 mm thick plate of AISI 304 steel. A commercial CO2 laser welding machine was equipped with a low-cost powder feeding system. In this work, following another one in which laser power, scanning speed and powder flow rate had been studied, the effects of two important process parameters, i.e. hatch spacing and step height, on the properties of the built parts were analysed. The explored ranges of hatch spacing and step height were respectively 150-300 μm and 100-200 μm, whose dimensions were comparable with that of the laser spot. The roughness, adhesion, microstructure, microhardness and density of the manufactured specimens were studied for multi-layer samples, which were made of 30 layers. The statistical significance of the studied process parameters was assessed by the analysis of the variance. The process parameters used allowed to obtain both first layer-to-substrate and layer-to-layer good adhesions. The microstructure was fine and almost defect-free. The microhardness of the deposited material was about 100 HV higher than that of the starting powder. The density as high as 98% of that of the same bulk alloy was more than satisfactory. Finally, simultaneous optimization of density and roughness was performed using the contour plots.

How Does Higher Frequency Monitoring Data Affect the Calibration of a Process-Based Water Quality Model?

NASA Astrophysics Data System (ADS)

Jackson-Blake, L.

2014-12-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, but even in well-studied catchments, streams are often only sampled at a fortnightly or monthly frequency. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by one process-based catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the MCMC-DREAM algorithm. Using daily rather than fortnightly data resulted in improved simulation of the magnitude of peak TDP concentrations, in turn resulting in improved model performance statistics. Marginal posteriors were better constrained by the higher frequency data, resulting in a large reduction in parameter-related uncertainty in simulated TDP (the 95% credible interval decreased from 26 to 6 μg/l). The number of parameters that could be reliably auto-calibrated was lower for the fortnightly data, leading to the recommendation that parameters should not be varied spatially for models such as INCA-P unless there is solid evidence that this is appropriate, or there is a real need to do so for the model to fulfil its purpose. Secondary study aims were to highlight the subjective elements involved in auto-calibration and suggest practical improvements that could make models such as INCA-P more suited to auto-calibration and uncertainty analyses. Two key improvements include model simplification, so that all model parameters can be included in an analysis of this kind, and better documenting of recommended ranges for each parameter, to help in choosing sensible priors.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Manufacturing a Porous Structure According to the Process Parameters of Functional 3D Porous Polymer Printing Technology Based on a Chemical Blowing Agent

NASA Astrophysics Data System (ADS)

Yoo, C. J.; Shin, B. S.; Kang, B. S.; Yun, D. H.; You, D. B.; Hong, S. M.

2017-09-01

In this paper, we propose a new porous polymer printing technology based on CBA(chemical blowing agent), and describe the optimization process according to the process parameters. By mixing polypropylene (PP) and CBA, a hybrid CBA filament was manufactured; the diameter of the filament ranged between 1.60 mm and 1.75 mm. A porous polymer structure was manufactured based on the traditional fused deposition modelling (FDM) method. The process parameters of the three-dimensional (3D) porous polymer printing (PPP) process included nozzle temperature, printing speed, and CBA density. Porosity increase with an increase in nozzle temperature and CBA density. On the contrary, porosity increase with a decrease in the printing speed. For porous structures, it has excellent mechanical properties. We manufactured a simple shape in 3D using 3D PPP technology. In the future, we will study the excellent mechanical properties of 3D PPP technology and apply them to various safety fields.

Trajectory Dispersed Vehicle Process for Space Launch System

NASA Technical Reports Server (NTRS)

Statham, Tamara; Thompson, Seth

2017-01-01

The Space Launch System (SLS) vehicle is part of NASA's deep space exploration plans that includes manned missions to Mars. Manufacturing uncertainties in design parameters are key considerations throughout SLS development as they have significant effects on focus parameters such as lift-off-thrust-to-weight, vehicle payload, maximum dynamic pressure, and compression loads. This presentation discusses how the SLS program captures these uncertainties by utilizing a 3 degree of freedom (DOF) process called Trajectory Dispersed (TD) analysis. This analysis biases nominal trajectories to identify extremes in the design parameters for various potential SLS configurations and missions. This process utilizes a Design of Experiments (DOE) and response surface methodologies (RSM) to statistically sample uncertainties, and develop resulting vehicles using a Maximum Likelihood Estimate (MLE) process for targeting uncertainties bias. These vehicles represent various missions and configurations which are used as key inputs into a variety of analyses in the SLS design process, including 6 DOF dispersions, separation clearances, and engine out failure studies.

Behavioral and Brain Measures of Phasic Alerting Effects on Visual Attention.

PubMed

Wiegand, Iris; Petersen, Anders; Finke, Kathrin; Bundesen, Claus; Lansner, Jon; Habekost, Thomas

2017-01-01

In the present study, we investigated effects of phasic alerting on visual attention in a partial report task, in which half of the displays were preceded by an auditory warning cue. Based on the computational Theory of Visual Attention (TVA), we estimated parameters of spatial and non-spatial aspects of visual attention and measured event-related lateralizations (ERLs) over visual processing areas. We found that the TVA parameter sensory effectiveness a , which is thought to reflect visual processing capacity, significantly increased with phasic alerting. By contrast, the distribution of visual processing resources according to task relevance and spatial position, as quantified in parameters top-down control α and spatial bias w index , was not modulated by phasic alerting. On the electrophysiological level, the latencies of ERLs in response to the task displays were reduced following the warning cue. These results suggest that phasic alerting facilitates visual processing in a general, unselective manner and that this effect originates in early stages of visual information processing.

Modeling and Experiment of Melt Impregnation of Continuous Fiber-reinforced Thermoplastic with Pins

NASA Astrophysics Data System (ADS)

Yang, Jian-Jun; Xin, Chun-Ling; Tang, Ke; Zhang, Zhi-Cheng; Yan, Bao-Rui; Ren, Feng; He, Ya-Dong

2016-05-01

Melt impregnation is a crucial method for continuous fiber-reinforced thermoplastic. It was developed several years ago for thermosetting plastic, but it is very popular now in the thermoplastic matrices, with a much higher viscosity. In this paper, we propose a mathematic model based on Darcy's law, which combined with processing parameters and material physical parameters. Then we use this model to predict the influence of processing parameters on the degree of impregnation of the prepreg, and the trend of prediction is consistent with the experimental results. Therefore, the exhaustive numerical study enables to define the optimal processing conditions for a perfect impregnation. The results are shown to be effective tools for finding optimal pulling speed, pin number and pressure for a given fluid/fibers pair.

Impact of process parameters on the breakage kinetics of poorly water-soluble drugs during wet stirred media milling: a microhydrodynamic view.

PubMed

Afolabi, Afolawemi; Akinlabi, Olakemi; Bilgili, Ecevit

2014-01-23

Wet stirred media milling has proven to be a robust process for producing nanoparticle suspensions of poorly water-soluble drugs. As the process is expensive and energy-intensive, it is important to study the breakage kinetics, which determines the cycle time and production rate for a desired fineness. Although the impact of process parameters on the properties of final product suspensions has been investigated, scant information is available regarding their impact on the breakage kinetics. Here, we elucidate the impact of stirrer speed, bead concentration, and drug loading on the breakage kinetics via a microhydrodynamic model for the bead-bead collisions. Suspensions of griseofulvin, a model poorly water-soluble drug, were prepared in the presence of two stabilizers: hydroxypropyl cellulose and sodium dodecyl sulfate. Laser diffraction, scanning electron microscopy, and rheometry were used to characterize them. Various microhydrodynamic parameters including a newly defined milling intensity factor was calculated. An increase in either the stirrer speed or the bead concentration led to an increase in the specific energy and the milling intensity factor, consequently faster breakage. On the other hand, an increase in the drug loading led to a decrease in these parameters and consequently slower breakage. While all microhydrodynamic parameters provided significant physical insight, only the milling intensity factor was capable of explaining the influence of all parameters directly through its strong correlation with the process time constant. Besides guiding process optimization, the analysis rationalizes the preparation of a single high drug-loaded batch (20% or higher) instead of multiple dilute batches. Copyright © 2013 Elsevier B.V. All rights reserved.

Downstream processing from hot-melt extrusion towards tablets: A quality by design approach.

PubMed

Grymonpré, W; Bostijn, N; Herck, S Van; Verstraete, G; Vanhoorne, V; Nuhn, L; Rombouts, P; Beer, T De; Remon, J P; Vervaet, C

2017-10-05

Since the concept of continuous processing is gaining momentum in pharmaceutical manufacturing, a thorough understanding on how process and formulation parameters can impact the critical quality attributes (CQA) of the end product is more than ever required. This study was designed to screen the influence of process parameters and drug load during HME on both extrudate properties and tableting behaviour of an amorphous solid dispersion formulation using a quality-by-design (QbD) approach. A full factorial experimental design with 19 experiments was used to evaluate the effect of several process variables (barrel temperature: 160-200°C, screw speed: 50-200rpm, throughput: 0.2-0.5kg/h) and drug load (0-20%) as formulation parameter on the hot-melt extrusion (HME) process, extrudate and tablet quality of Soluplus ® -Celecoxib amorphous solid dispersions. A prominent impact of the formulation parameter on the CQA of the extrudates (i.e. solid state properties, moisture content, particle size distribution) and tablets (i.e. tabletability, compactibility, fragmentary behaviour, elastic recovery) was discovered. The resistance of the polymer matrix to thermo-mechanical stress during HME was confirmed throughout the experimental design space. In addition, the suitability of Raman spectroscopy as verification method for the active pharmaceutical ingredient (API) concentration in solid dispersions was evaluated. Incorporation of the Raman spectroscopy data in a PLS model enabled API quantification in the extrudate powders with none of the DOE-experiments resulting in extrudates with a CEL content deviating>3% of the label claim. This research paper emphasized that HME is a robust process throughout the experimental design space for obtaining amorphous glassy solutions and for tabletting of such formulations since only minimal impact of the process parameters was detected on the extrudate and tablet properties. However, the quality of extrudates and tablets can be optimized by adjusting specific formulations parameters (e.g. drug load). Copyright © 2017 Elsevier B.V. All rights reserved.

Applicability of Different Hydraulic Parameters to Describe Soil Detachment in Eroding Rills

PubMed Central

Wirtz, Stefan; Seeger, Manuel; Zell, Andreas; Wagner, Christian; Wagner, Jean-Frank; Ries, Johannes B.

2013-01-01

This study presents the comparison of experimental results with assumptions used in numerical models. The aim of the field experiments is to test the linear relationship between different hydraulic parameters and soil detachment. For example correlations between shear stress, unit length shear force, stream power, unit stream power and effective stream power and the detachment rate does not reveal a single parameter which consistently displays the best correlation. More importantly, the best fit does not only vary from one experiment to another, but even between distinct measurement points. Different processes in rill erosion are responsible for the changing correlations. However, not all these procedures are considered in soil erosion models. Hence, hydraulic parameters alone are not sufficient to predict detachment rates. They predict the fluvial incising in the rill's bottom, but the main sediment sources are not considered sufficiently in its equations. The results of this study show that there is still a lack of understanding of the physical processes underlying soil erosion. Exerted forces, soil stability and its expression, the abstraction of the detachment and transport processes in shallow flowing water remain still subject of unclear description and dependence. PMID:23717669

Transient Oscilliations in Mechanical Systems of Automatic Control with Random Parameters

NASA Astrophysics Data System (ADS)

Royev, B.; Vinokur, A.; Kulikov, G.

2018-04-01

Transient oscillations in mechanical systems of automatic control with random parameters is a relevant but insufficiently studied issue. In this paper, a modified spectral method was applied to investigate the problem. The nature of dynamic processes and the phase portraits are analyzed depending on the amplitude and frequency of external influence. It is evident from the obtained results, that the dynamic phenomena occurring in the systems with random parameters under external influence are complex, and their study requires further investigation.

GRCop-84 Rolling Parameter Study

NASA Technical Reports Server (NTRS)

Loewenthal, William S.; Ellis, David L.

2008-01-01

This report is a section of the final report on the GRCop-84 task of the Constellation Program and incorporates the results obtained between October 2000 and September 2005, when the program ended. NASA Glenn Research Center (GRC) has developed a new copper alloy, GRCop-84 (Cu-8 at.% Cr-4 at.% Nb), for rocket engine main combustion chamber components that will improve rocket engine life and performance. This work examines the sensitivity of GRCop-84 mechanical properties to rolling parameters as a means to better define rolling parameters for commercial warm rolling. Experiment variables studied were total reduction, rolling temperature, rolling speed, and post rolling annealing heat treatment. The responses were tensile properties measured at 23 and 500 C, hardness, and creep at three stress-temperature combinations. Understanding these relationships will better define boundaries for a robust commercial warm rolling process. The four processing parameters were varied within limits consistent with typical commercial production processes. Testing revealed that the rolling-related variables selected have a minimal influence on tensile, hardness, and creep properties over the range of values tested. Annealing had the expected result of lowering room temperature hardness and strength while increasing room temperature elongations with 600 C (1112 F) having the most effect. These results indicate that the process conditions to warm roll plate and sheet for these variables can range over wide levels without negatively impacting mechanical properties. Incorporating broader process ranges in future rolling campaigns should lower commercial rolling costs through increased productivity.

The study of optimization on process parameters of high-accuracy computerized numerical control polishing

NASA Astrophysics Data System (ADS)

Huang, Wei-Ren; Huang, Shih-Pu; Tsai, Tsung-Yueh; Lin, Yi-Jyun; Yu, Zong-Ru; Kuo, Ching-Hsiang; Hsu, Wei-Yao; Young, Hong-Tsu

2017-09-01

Spherical lenses lead to forming spherical aberration and reduced optical performance. Consequently, in practice optical system shall apply a combination of spherical lenses for aberration correction. Thus, the volume of the optical system increased. In modern optical systems, aspherical lenses have been widely used because of their high optical performance with less optical components. However, aspherical surfaces cannot be fabricated by traditional full aperture polishing process due to their varying curvature. Sub-aperture computer numerical control (CNC) polishing is adopted for aspherical surface fabrication in recent years. By using CNC polishing process, mid-spatial frequency (MSF) error is normally accompanied during this process. And the MSF surface texture of optics decreases the optical performance for high precision optical system, especially for short-wavelength applications. Based on a bonnet polishing CNC machine, this study focuses on the relationship between MSF surface texture and CNC polishing parameters, which include feed rate, head speed, track spacing and path direction. The power spectral density (PSD) analysis is used to judge the MSF level caused by those polishing parameters. The test results show that controlling the removal depth of single polishing path, through the feed rate, and without same direction polishing path for higher total removal depth can efficiently reduce the MSF error. To verify the optical polishing parameters, we divided a correction polishing process to several polishing runs with different direction polishing paths. Compare to one shot polishing run, multi-direction path polishing plan could produce better surface quality on the optics.

Hyperbolic Discounting: Value and Time Processes of Substance Abusers and Non-Clinical Individuals in Intertemporal Choice

PubMed Central

2014-01-01

The single parameter hyperbolic model has been frequently used to describe value discounting as a function of time and to differentiate substance abusers and non-clinical participants with the model's parameter k. However, k says little about the mechanisms underlying the observed differences. The present study evaluates several alternative models with the purpose of identifying whether group differences stem from differences in subjective valuation, and/or time perceptions. Using three two-parameter models, plus secondary data analyses of 14 studies with 471 indifference point curves, results demonstrated that adding a valuation, or a time perception function led to better model fits. However, the gain in fit due to the flexibility granted by a second parameter did not always lead to a better understanding of the data patterns and corresponding psychological processes. The k parameter consistently indexed group and context (magnitude) differences; it is thus a mixed measure of person and task level effects. This was similar for a parameter meant to index payoff devaluation. A time perception parameter, on the other hand, fluctuated with contexts in a non-predicted fashion and the interpretation of its values was inconsistent with prior findings that supported enlarged perceived delays for substance abusers compared to controls. Overall, the results provide mixed support for hyperbolic models of intertemporal choice in terms of the psychological meaning afforded by their parameters. PMID:25390941

Study on super-long deep-hole drilling of titanium alloy.

PubMed

Liu, Zhanfeng; Liu, Yanshu; Han, Xiaolan; Zheng, Wencui

2018-01-01

In this study, the super-long deep-hole drilling of a titanium alloy was investigated. According to material properties of the titanium alloy, an experimental approach was designed to study three issues discovered during the drilling process: the hole-axis deflection, chip morphology, and tool wear. Based on the results of drilling experiments, crucial parameters for the super-long deep-hole drilling of titanium alloys were obtained, and the influences of these parameters on quality of the alloy's machining were also evaluated. Our results suggest that the developed drilling process is an effective method to overcome the challenge of super-long deep-hole drilling on difficult-to-cut materials.

Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones.

PubMed

Cardin, Velia; Orfanidou, Eleni; Kästner, Lena; Rönnberg, Jerker; Woll, Bencie; Capek, Cheryl M; Rudner, Mary

2016-01-01

The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.

Swarm size and iteration number effects to the performance of PSO algorithm in RFID tag coverage optimization

NASA Astrophysics Data System (ADS)

Prathabrao, M.; Nawawi, Azli; Sidek, Noor Azizah

2017-04-01

Radio Frequency Identification (RFID) system has multiple benefits which can improve the operational efficiency of the organization. The advantages are the ability to record data systematically and quickly, reducing human errors and system errors, update the database automatically and efficiently. It is often more readers (reader) is needed for the installation purposes in RFID system. Thus, it makes the system more complex. As a result, RFID network planning process is needed to ensure the RFID system works perfectly. The planning process is also considered as an optimization process and power adjustment because the coordinates of each RFID reader to be determined. Therefore, algorithms inspired by the environment (Algorithm Inspired by Nature) is often used. In the study, PSO algorithm is used because it has few number of parameters, the simulation time is fast, easy to use and also very practical. However, PSO parameters must be adjusted correctly, for robust and efficient usage of PSO. Failure to do so may result in disruption of performance and results of PSO optimization of the system will be less good. To ensure the efficiency of PSO, this study will examine the effects of two parameters on the performance of PSO Algorithm in RFID tag coverage optimization. The parameters to be studied are the swarm size and iteration number. In addition to that, the study will also recommend the most optimal adjustment for both parameters that is, 200 for the no. iterations and 800 for the no. of swarms. Finally, the results of this study will enable PSO to operate more efficiently in order to optimize RFID network planning system.

Optimization and Simulation of Plastic Injection Process using Genetic Algorithm and Moldflow

NASA Astrophysics Data System (ADS)

Martowibowo, Sigit Yoewono; Kaswadi, Agung

2017-03-01

The use of plastic-based products is continuously increasing. The increasing demands for thinner products, lower production costs, yet higher product quality has triggered an increase in the number of research projects on plastic molding processes. An important branch of such research is focused on mold cooling system. Conventional cooling systems are most widely used because they are easy to make by using conventional machining processes. However, the non-uniform cooling processes are considered as one of their weaknesses. Apart from the conventional systems, there are also conformal cooling systems that are designed for faster and more uniform plastic mold cooling. In this study, the conformal cooling system is applied for the production of bowl-shaped product made of PP AZ564. Optimization is conducted to initiate machine setup parameters, namely, the melting temperature, injection pressure, holding pressure and holding time. The genetic algorithm method and Moldflow were used to optimize the injection process parameters at a minimum cycle time. It is found that, an optimum injection molding processes could be obtained by setting the parameters to the following values: T M = 180 °C; P inj = 20 MPa; P hold = 16 MPa and t hold = 8 s, with a cycle time of 14.11 s. Experiments using the conformal cooling system yielded an average cycle time of 14.19 s. The studied conformal cooling system yielded a volumetric shrinkage of 5.61% and the wall shear stress was found at 0.17 MPa. The difference between the cycle time obtained through simulations and experiments using the conformal cooling system was insignificant (below 1%). Thus, combining process parameters optimization and simulations by using genetic algorithm method with Moldflow can be considered as valid.

Continuous separation of copper ions from a mixture of heavy metal ions using a three-zone carousel process packed with metal ion-imprinted polymer.

PubMed

Jo, Se-Hee; Lee, See-Young; Park, Kyeong-Mok; Yi, Sung Chul; Kim, Dukjoon; Mun, Sungyong

2010-11-05

In this study, a three-zone carousel process based on a proper molecular imprinted polymer (MIP) resin was developed for continuous separation of Cu(2+) from Mn(2+) and Co(2+). For this task, the Cu (II)-imprinted polymer (Cu-MIP) resin was synthesized first and used to pack the chromatographic columns of a three-zone carousel process. Prior to the experiment of the carousel process based on the Cu-MIP resin (MIP-carousel process), a series of single-column experiments were performed to estimate the intrinsic parameters of the three heavy metal ions and to find out the appropriate conditions of regeneration and re-equilibration. The results from these single-column experiments and the additional computer simulations were then used for determination of the operating parameters of the MIP-carousel process under consideration. Based on the determined operating parameters, the MIP-carousel experiments were carried out. It was confirmed from the experimental results that the proposed MIP-carousel process was markedly effective in separating Cu(2+) from Mn(2+) and Co(2+) in a continuous mode with high purity and a relatively small loss. Thus, the MIP-carousel process developed in this study deserves sufficient attention in materials processing industries or metal-related industries, where the selective separation of heavy metal ions with the same charge has been a major concern. Copyright © 2010 Elsevier B.V. All rights reserved.

A Design of Experiments Approach Defining the Relationships Between Processing and Microstructure for Ti-6Al-4V

NASA Technical Reports Server (NTRS)

Wallace, Terryl A.; Bey, Kim S.; Taminger, Karen M. B.; Hafley, Robert A.

2004-01-01

A study was conducted to evaluate the relative significance of input parameters on Ti- 6Al-4V deposits produced by an electron beam free form fabrication process under development at the NASA Langley Research Center. Five input parameters where chosen (beam voltage, beam current, translation speed, wire feed rate, and beam focus), and a design of experiments (DOE) approach was used to develop a set of 16 experiments to evaluate the relative importance of these parameters on the resulting deposits. Both single-bead and multi-bead stacks were fabricated using 16 combinations, and the resulting heights and widths of the stack deposits were measured. The resulting microstructures were also characterized to determine the impact of these parameters on the size of the melt pool and heat affected zone. The relative importance of each input parameter on the height and width of the multi-bead stacks will be discussed. .

Effective Parameters in Axial Injection Suspension Plasma Spray Process of Alumina-Zirconia Ceramics

NASA Astrophysics Data System (ADS)

Tarasi, F.; Medraj, M.; Dolatabadi, A.; Oberste-Berghaus, J.; Moreau, C.

2008-12-01

Suspension plasma spray (SPS) is a novel process for producing nano-structured coatings with metastable phases using significantly smaller particles as compared to conventional thermal spraying. Considering the complexity of the system there is an extensive need to better understand the relationship between plasma spray conditions and resulting coating microstructure and defects. In this study, an alumina/8 wt.% yttria-stabilized zirconia was deposited by axial injection SPS process. The effects of principal deposition parameters on the microstructural features are evaluated using the Taguchi design of experiment. The microstructural features include microcracks, porosities, and deposition rate. To better understand the role of the spray parameters, in-flight particle characteristics, i.e., temperature and velocity were also measured. The role of the porosity in this multicomponent structure is studied as well. The results indicate that thermal diffusivity of the coatings, an important property for potential thermal barrier applications, is barely affected by the changes in porosity content.

Dynamic Computation of Change Operations in Version Management of Business Process Models

NASA Astrophysics Data System (ADS)

Küster, Jochen Malte; Gerth, Christian; Engels, Gregor

Version management of business process models requires that changes can be resolved by applying change operations. In order to give a user maximal freedom concerning the application order of change operations, position parameters of change operations must be computed dynamically during change resolution. In such an approach, change operations with computed position parameters must be applicable on the model and dependencies and conflicts of change operations must be taken into account because otherwise invalid models can be constructed. In this paper, we study the concept of partially specified change operations where parameters are computed dynamically. We provide a formalization for partially specified change operations using graph transformation and provide a concept for their applicability. Based on this, we study potential dependencies and conflicts of change operations and show how these can be taken into account within change resolution. Using our approach, a user can resolve changes of business process models without being unnecessarily restricted to a certain order.

Effect of fermentation parameters on bio-alcohols production from glycerol using immobilized Clostridium pasteurianum: an optimization study.

PubMed

Khanna, Swati; Goyal, Arun; Moholkar, Vijayanand S

2013-01-01

This article addresses the issue of effect of fermentation parameters for conversion of glycerol (in both pure and crude form) into three value-added products, namely, ethanol, butanol, and 1,3-propanediol (1,3-PDO), by immobilized Clostridium pasteurianum and thereby addresses the statistical optimization of this process. The analysis of effect of different process parameters such as agitation rate, fermentation temperature, medium pH, and initial glycerol concentration indicated that medium pH was the most critical factor for total alcohols production in case of pure glycerol as fermentation substrate. On the other hand, initial glycerol concentration was the most significant factor for fermentation with crude glycerol. An interesting observation was that the optimized set of fermentation parameters was found to be independent of the type of glycerol (either pure or crude) used. At optimum conditions of agitation rate (200 rpm), initial glycerol concentration (25 g/L), fermentation temperature (30°C), and medium pH (7.0), the total alcohols production was almost equal in anaerobic shake flasks and 2-L bioreactor. This essentially means that at optimum process parameters, the scale of operation does not affect the output of the process. The immobilized cells could be reused for multiple cycles for both pure and crude glycerol fermentation.

Predictive Modeling and Optimization of Vibration-assisted AFM Tip-based Nanomachining

NASA Astrophysics Data System (ADS)

Kong, Xiangcheng

The tip-based vibration-assisted nanomachining process offers a low-cost, low-effort technique in fabricating nanometer scale 2D/3D structures in sub-100 nm regime. To understand its mechanism, as well as provide the guidelines for process planning and optimization, we have systematically studied this nanomachining technique in this work. To understand the mechanism of this nanomachining technique, we firstly analyzed the interaction between the AFM tip and the workpiece surface during the machining process. A 3D voxel-based numerical algorithm has been developed to calculate the material removal rate as well as the contact area between the AFM tip and the workpiece surface. As a critical factor to understand the mechanism of this nanomachining process, the cutting force has been analyzed and modeled. A semi-empirical model has been proposed by correlating the cutting force with the material removal rate, which was validated using experimental data from different machining conditions. With the understanding of its mechanism, we have developed guidelines for process planning of this nanomachining technique. To provide the guideline for parameter selection, the effect of machining parameters on the feature dimensions (depth and width) has been analyzed. Based on ANOVA test results, the feature width is only controlled by the XY vibration amplitude, while the feature depth is affected by several machining parameters such as setpoint force and feed rate. A semi-empirical model was first proposed to predict the machined feature depth under given machining condition. Then, to reduce the computation intensity, linear and nonlinear regression models were also proposed and validated using experimental data. Given the desired feature dimensions, feasible machining parameters could be provided using these predictive feature dimension models. As the tip wear is unavoidable during the machining process, the machining precision will gradually decrease. To maintain the machining quality, the guideline for when to change the tip should be provided. In this study, we have developed several metrics to detect tip wear, such as tip radius and the pull-off force. The effect of machining parameters on the tip wear rate has been studied using these metrics, and the machining distance before a tip must be changed has been modeled using these machining parameters. Finally, the optimization functions have been built for unit production time and unit production cost subject to realistic constraints, and the optimal machining parameters can be found by solving these functions.

Optimal design study of high efficiency indium phosphide space solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

Recently indium phosphide solar cells have achieved beginning of life AMO efficiencies in excess of 19 pct. at 25 C. The high efficiency prospects along with superb radiation tolerance make indium phosphide a leading material for space power requirements. To achieve cost effectiveness, practical cell efficiencies have to be raised to near theoretical limits and thin film indium phosphide cells need to be developed. The optimal design study is described of high efficiency indium phosphide solar cells for space power applications using the PC-1D computer program. It is shown that cells with efficiencies over 22 pct. AMO at 25 C could be fabricated by achieving proper material and process parameters. It is observed that further improvements in cell material and process parameters could lead to experimental cell efficiencies near theoretical limits. The effect of various emitter and base parameters on cell performance was studied.

Monitoring early hydration of reinforced concrete structures using structural parameters identified by piezo sensors via electromechanical impedance technique

NASA Astrophysics Data System (ADS)

Talakokula, Visalakshi; Bhalla, Suresh; Gupta, Ashok

2018-01-01

Concrete is the most widely used material in civil engineering construction. Its life begins when the hydration process is activated after mixing the cement granulates with water. In this paper, a non-dimensional hydration parameter, obtained from piezoelectric ceramic (PZT) patches bonded to rebars embedded inside concrete, is employed to monitor the early age hydration of concrete. The non-dimensional hydration parameter is derived from the equivalent stiffness determined from the piezo-impedance transducers using the electro-mechanical impedance (EMI) technique. The focus of the study is to monitor the hydration process of cementitious materials commencing from the early hours and continue till 28 days using single non-dimensional parameter. The experimental results show that the proposed piezo-based non-dimensional hydration parameter is very effective in monitoring the early age hydration, as it has been derived from the refined structural impedance parameters, obtained by eliminating the PZT contribution, and using both the real and imaginary components of the admittance signature.

The effect of orientation difference in fused deposition modeling of ABS polymer on the processing time, dimension accuracy, and strength

NASA Astrophysics Data System (ADS)

Tanoto, Yopi Y.; Anggono, Juliana; Siahaan, Ian H.; Budiman, Wesley

2017-01-01

There are several parameters that must be set before manufacturing a product using 3D printing. These parameters include the orientation deposition of that product, type of material, form fill, fill density, and other parameters. The finished product of 3D printing has some responses that can be observed, measured, and tested. Some of those responses are the processing time, the dimensions of the end product, its surface roughness and the mechanical properties, i.e. its yield strength, ultimate tensile strength, and impact resistance. This research was conducted to study the relationship between process parameters of 3D printing machine using a technology of fused deposition modeling (FDM) and the generated responses. The material used was ABS plastic that was commonly used in the industry. Understanding the relationship between the parameters and the responses thus the resulting product can be manufactured to meet the user needs. Three different orientations in depositing the ABS polymer named XY(first orientation), YX (second orientation), and ZX (third orientation) were studied. Processing time, dimensional accuracy, and the product strength were the responses that were measured and tested. The study reports that the printing process with third orientation was the fastest printing process with the processing time 2432 seconds followed by orientation 1 and 2 with a processing time of 2688 and 2780 seconds respectively. Dimension accuracy was also measured from the width and the length of gauge area of tensile test specimens printed in comparison with the dimensions required by ASTM 638-02. It was found that the smallest difference was in thickness dimension, i.e. 0.1 mm thicker in printed sample using second orientation than as required by the standard. The smallest thickness deviation from the standard was measured in width dimension of a sample printed using first orientation (0.13 mm). As with the length dimension, the closest dimension to the standard was resulted from the third orientation product, i.e 0.2 mm. Tensile test done on all the specimens produced with those three orientations shows that the highest tensile strength was obtained in sample from second orientation deposition, i.e. 7.66 MPa followed by the first and third orientations products, i.e. 6.8 MPa and 3.31 MPa, respectively.

Optimization of Dimensional accuracy in plasma arc cutting process employing parametric modelling approach

NASA Astrophysics Data System (ADS)

Naik, Deepak kumar; Maity, K. P.

2018-03-01

Plasma arc cutting (PAC) is a high temperature thermal cutting process employed for the cutting of extensively high strength material which are difficult to cut through any other manufacturing process. This process involves high energized plasma arc to cut any conducting material with better dimensional accuracy in lesser time. This research work presents the effect of process parameter on to the dimensional accuracy of PAC process. The input process parameters were selected as arc voltage, standoff distance and cutting speed. A rectangular plate of 304L stainless steel of 10 mm thickness was taken for the experiment as a workpiece. Stainless steel is very extensively used material in manufacturing industries. Linear dimension were measured following Taguchi’s L16 orthogonal array design approach. Three levels were selected to conduct the experiment for each of the process parameter. In all experiments, clockwise cut direction was followed. The result obtained thorough measurement is further analyzed. Analysis of variance (ANOVA) and Analysis of means (ANOM) were performed to evaluate the effect of each process parameter. ANOVA analysis reveals the effect of input process parameter upon leaner dimension in X axis. The results of the work shows that the optimal setting of process parameter values for the leaner dimension on the X axis. The result of the investigations clearly show that the specific range of input process parameter achieved the improved machinability.

Study on validation method for femur finite element model under multiple loading conditions

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu

2018-03-01

Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.

Optimization and Analysis of Laser Beam Machining Parameters for Al7075-TiB2 In-situ Composite

NASA Astrophysics Data System (ADS)

Manjoth, S.; Keshavamurthy, R.; Pradeep Kumar, G. S.

2016-09-01

The paper focuses on laser beam machining (LBM) of In-situ synthesized Al7075-TiB2 metal matrix composite. Optimization and influence of laser machining process parameters on surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy of composites were studied. Al7075-TiB2 metal matrix composite was synthesized by in-situ reaction technique using stir casting process. Taguchi's L9 orthogonal array was used to design experimental trials. Standoff distance (SOD) (0.3 - 0.5mm), Cutting Speed (1000 - 1200 m/hr) and Gas pressure (0.5 - 0.7 bar) were considered as variable input parameters at three different levels, while power and nozzle diameter were maintained constant with air as assisting gas. Optimized process parameters for surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy were calculated by generating the main effects plot for signal noise ratio (S/N ratio) for surface roughness, VMRR and dimensional error using Minitab software (version 16). The Significant of standoff distance (SOD), cutting speed and gas pressure on surface roughness, volumetric material removal rate (VMRR) and dimensional error were calculated using analysis of variance (ANOVA) method. Results indicate that, for surface roughness, cutting speed (56.38%) is most significant parameter followed by standoff distance (41.03%) and gas pressure (2.6%). For volumetric material removal (VMRR), gas pressure (42.32%) is most significant parameter followed by cutting speed (33.60%) and standoff distance (24.06%). For dimensional error, Standoff distance (53.34%) is most significant parameter followed by cutting speed (34.12%) and gas pressure (12.53%). Further, verification experiments were carried out to confirm performance of optimized process parameters.

Simulation of aerobic and anaerobic biodegradation processes at a crude oil spill site

USGS Publications Warehouse

Essaid, Hedeff I.; Bekins, Barbara A.; Godsy, E. Michael; Warren, Ean; Baedecker, Mary Jo; Cozzarelli, Isabelle M.

1995-01-01

A two-dimensional, multispecies reactive solute transport model with sequential aerobic and anaerobic degradation processes was developed and tested. The model was used to study the field-scale solute transport and degradation processes at the Bemidji, Minnesota, crude oil spill site. The simulations included the biodegradation of volatile and nonvolatile fractions of dissolved organic carbon by aerobic processes, manganese and iron reduction, and methanogenesis. Model parameter estimates were constrained by published Monod kinetic parameters, theoretical yield estimates, and field biomass measurements. Despite the considerable uncertainty in the model parameter estimates, results of simulations reproduced the general features of the observed groundwater plume and the measured bacterial concentrations. In the simulation, 46% of the total dissolved organic carbon (TDOC) introduced into the aquifer was degraded. Aerobic degradation accounted for 40% of the TDOC degraded. Anaerobic processes accounted for the remaining 60% of degradation of TDOC: 5% by Mn reduction, 19% by Fe reduction, and 36% by methanogenesis. Thus anaerobic processes account for more than half of the removal of DOC at this site.

Production Process of Biocompatible Magnesium Alloy Tubes Using Extrusion and Dieless Drawing Processes

NASA Astrophysics Data System (ADS)

Kustra, Piotr; Milenin, Andrij; Płonka, Bartłomiej; Furushima, Tsuyoshi

2016-06-01

Development of technological production process of biocompatible magnesium tubes for medical applications is the subject of the present paper. The technology consists of two stages—extrusion and dieless drawing process, respectively. Mg alloys for medical applications such as MgCa0.8 are characterized by low technological plasticity during deformation that is why optimization of production parameters is necessary to obtain good quality product. Thus, authors developed yield stress and ductility model for the investigated Mg alloy and then used the numerical simulations to evaluate proper manufacturing conditions. Grid Extrusion3d software developed by authors was used to determine optimum process parameters for extrusion—billet temperature 400 °C and extrusion velocity 1 mm/s. Based on those parameters the tube with external diameter 5 mm without defects was manufactured. Then, commercial Abaqus software was used for modeling dieless drawing. It was shown that the reduction in the area of 60% can be realized for MgCa0.8 magnesium alloy. Tubes with the final diameter of 3 mm were selected as a case study, to present capabilities of proposed processes.

Modeling microbiological and chemical processes in municipal solid waste bioreactor, Part II: Application of numerical model BIOKEMOD-3P.

PubMed

Gawande, Nitin A; Reinhart, Debra R; Yeh, Gour-Tsyh

2010-02-01

Biodegradation process modeling of municipal solid waste (MSW) bioreactor landfills requires the knowledge of various process reactions and corresponding kinetic parameters. Mechanistic models available to date are able to simulate biodegradation processes with the help of pre-defined species and reactions. Some of these models consider the effect of critical parameters such as moisture content, pH, and temperature. Biomass concentration is a vital parameter for any biomass growth model and often not compared with field and laboratory results. A more complex biodegradation model includes a large number of chemical and microbiological species. Increasing the number of species and user defined process reactions in the simulation requires a robust numerical tool. A generalized microbiological and chemical model, BIOKEMOD-3P, was developed to simulate biodegradation processes in three-phases (Gawande et al. 2009). This paper presents the application of this model to simulate laboratory-scale MSW bioreactors under anaerobic conditions. BIOKEMOD-3P was able to closely simulate the experimental data. The results from this study may help in application of this model to full-scale landfill operation.

A Parameter Tuning Scheme of Sea-ice Model Based on Automatic Differentiation Technique

NASA Astrophysics Data System (ADS)

Kim, J. G.; Hovland, P. D.

2001-05-01

Automatic diferentiation (AD) technique was used to illustrate a new approach for parameter tuning scheme of an uncoupled sea-ice model. Atmospheric forcing field of 1992 obtained from NCEP data was used as enforcing variables in the study. The simulation results were compared with the observed ice movement provided by the International Arctic Buoy Programme (IABP). All of the numerical experiments were based on a widely used dynamic and thermodynamic model for simulating the seasonal sea-ice chnage of the main Arctic ocean. We selected five dynamic and thermodynamic parameters for the tuning process in which the cost function defined by the norm of the difference between observed and simulated ice drift locations was minimized. The selected parameters are the air and ocean drag coefficients, the ice strength constant, the turning angle at ice-air/ocean interface, and the bulk sensible heat transfer coefficient. The drag coefficients were the major parameters to control sea-ice movement and extent. The result of the study shows that more realistic simulations of ice thickness distribution was produced by tuning the simulated ice drift trajectories. In the tuning process, the L-BFCGS-B minimization algorithm of a quasi-Newton method was used. The derivative information required in the minimization iterations was provided by the AD processed Fortran code. Compared with a conventional approach, AD generated derivative code provided fast and robust computations of derivative information.

Method and apparatus for assessing weld quality

DOEpatents

Smartt, Herschel B.; Kenney, Kevin L.; Johnson, John A.; Carlson, Nancy M.; Clark, Denis E.; Taylor, Paul L.; Reutzel, Edward W.

2001-01-01

Apparatus for determining a quality of a weld produced by a welding device according to the present invention includes a sensor operatively associated with the welding device. The sensor is responsive to at least one welding process parameter during a welding process and produces a welding process parameter signal that relates to the at least one welding process parameter. A computer connected to the sensor is responsive to the welding process parameter signal produced by the sensor. A user interface operatively associated with the computer allows a user to select a desired welding process. The computer processes the welding process parameter signal produced by the sensor in accordance with one of a constant voltage algorithm, a short duration weld algorithm or a pulsed current analysis module depending on the desired welding process selected by the user. The computer produces output data indicative of the quality of the weld.

Reflow dynamics of thin patterned viscous films

NASA Astrophysics Data System (ADS)

Leveder, T.; Landis, S.; Davoust, L.

2008-01-01

This letter presents a study of viscous smoothening dynamics of a nanopatterned thin film. Ultrathin film manufacturing processes appearing to be a key point of nanotechnology engineering and numerous studies have been recently led in order to exhibit driving parameters of this transient surface motion, focusing on time scale accuracy method. Based on nanomechanical analysis, this letter shows that controlled shape measurements provided much more detailed information about reflow mechanism. Control of reflow process of any complex surface shape, or measurement of material parameter as thin film viscosity, free surface energy, or even Hamaker constant are therefore possible.

Interhemispheric and Intrahemispheric Control of Emotion: A Focus on Unilateral Brain Damage.

ERIC Educational Resources Information Center

Borod, Joan C.

1992-01-01

Discusses neocortical contributions to emotional processing. Examines parameters critical to neuropsychological study of emotion: interhemispheric and intrahemispheric factors, processing mode, and communication channel. Describes neuropsychological theories of emotion. Reviews studies of right-brain-damaged, left-brain-damaged, and normal adults,…

Study on feed forward neural network convex optimization for LiFePO4 battery parameters

NASA Astrophysics Data System (ADS)

Liu, Xuepeng; Zhao, Dongmei

2017-08-01

Based on the modern facility agriculture automatic walking equipment LiFePO4 Battery, the parameter identification of LiFePO4 Battery is analyzed. An improved method for the process model of li battery is proposed, and the on-line estimation algorithm is presented. The parameters of the battery are identified using feed forward network neural convex optimization algorithm.

Modeling urbanized watershed flood response changes with distributed hydrological model: key hydrological processes, parameterization and case studies

NASA Astrophysics Data System (ADS)

Chen, Y.

2017-12-01

Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to urbanization, and the results show urbanization has big impact on the watershed flood responses. The peak flow increased a few times after urbanization which is much higher than previous reports.

Experimental and numerical study on optimization of the single point incremental forming of AINSI 304L stainless steel sheet

NASA Astrophysics Data System (ADS)

Saidi, B.; Giraud-Moreau, L.; Cherouat, A.; Nasri, R.

2017-09-01

AINSI 304L stainless steel sheets are commonly formed into a variety of shapes for applications in the industrial, architectural, transportation and automobile fields, it’s also used for manufacturing of denture base. In the field of dentistry, there is a need for personalized devises that are custom made for the patient. The single point incremental forming process is highly promising in this area for manufacturing of denture base. The single point incremental forming process (ISF) is an emerging process based on the use of a spherical tool, which is moved along CNC controlled tool path. One of the major advantages of this process is the ability to program several punch trajectories on the same machine in order to obtain different shapes. Several applications of this process exist in the medical field for the manufacturing of personalized titanium prosthesis (cranial plate, knee prosthesis...) due to the need of product customization to each patient. The objective of this paper is to study the incremental forming of AISI 304L stainless steel sheets for future applications in the dentistry field. During the incremental forming process, considerable forces can occur. The control of the forming force is particularly important to ensure the safe use of the CNC milling machine and preserve the tooling and machinery. In this paper, the effect of four different process parameters on the maximum force is studied. The proposed approach consists in using an experimental design based on experimental results. An analysis of variance was conducted with ANOVA to find the input parameters allowing to minimize the maximum forming force. A numerical simulation of the incremental forming process is performed with the optimal input process parameters. Numerical results are compared with the experimental ones.

Ring rolling process simulation for microstructure optimization

NASA Astrophysics Data System (ADS)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Metal undergoes complicated microstructural evolution during Hot Ring Rolling (HRR), which determines the quality, mechanical properties and life of the ring formed. One of the principal microstructure properties which mostly influences the structural performances of forged components, is the value of the average grain size. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular velocity of driver roll) on microstructural and on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR has been developed in SFTC DEFORM V11, taking into account also microstructural development of the material used (the nickel superalloy Waspalloy). The Finite Element (FE) model has been used to formulate a proper optimization problem. The optimization procedure has been developed in order to find the combination of process parameters which allows to minimize the average grain size. The Response Surface Methodology (RSM) has been used to find the relationship between input and output parameters, by using the exact values of output parameters in the control points of a design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. Then, an optimization procedure based on Genetic Algorithms has been applied. At the end, the minimum value of average grain size with respect to the input parameters has been found.

Individual differences in emotion processing: how similar are diffusion model parameters across tasks?

PubMed

Mueller, Christina J; White, Corey N; Kuchinke, Lars

2017-11-27

The goal of this study was to replicate findings of diffusion model parameters capturing emotion effects in a lexical decision task and investigating whether these findings extend to other tasks of implicit emotion processing. Additionally, we were interested in the stability of diffusion model parameters across emotional stimuli and tasks for individual subjects. Responses to words in a lexical decision task were compared with responses to faces in a gender categorization task for stimuli of the emotion categories: happy, neutral and fear. Main effects of emotion as well as stability of emerging response style patterns as evident in diffusion model parameters across these tasks were analyzed. Based on earlier findings, drift rates were assumed to be more similar in response to stimuli of the same emotion category compared to stimuli of a different emotion category. Results showed that emotion effects of the tasks differed with a processing advantage for happy followed by neutral and fear-related words in the lexical decision task and a processing advantage for neutral followed by happy and fearful faces in the gender categorization task. Both emotion effects were captured in estimated drift rate parameters-and in case of the lexical decision task also in the non-decision time parameters. A principal component analysis showed that contrary to our hypothesis drift rates were more similar within a specific task context than within a specific emotion category. Individual response patterns of subjects across tasks were evident in significant correlations regarding diffusion model parameters including response styles, non-decision times and information accumulation.

Computer-aided method for the determination of Hansen solubility parameters. Application to the miscibility of refrigerating lubricant and new refrigerant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Remigy, J.C.; Nakache, E.; Brechot, P.D.

This article presents a method which allows one to find the Hansen solubility parameters by means of data processing. In the first part, the authors present the thermodynamical principle of Hansen parameters, and then they explain the model used to find parameters from experimental data. They validate the method by studying the solubility parameters of CFC-12 (dichlorodifluoromethane), HFC-134a (1,1,1,2-tetrafluoroethane), neopentylglycol esters, trimethylolpropane esters, dipentaerythritol esters, and pentaerythritol esters. Then, the variation of Hansen parameters are studied as well as the relation between the miscibility temperature (the temperature at which a blend passes from the miscible state to the immiscible state)more » and the interaction distance. The authors establish the critical interaction distance of HFC-134a which determines the solubility limit and they study its variation with temperature.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sai, P.M.S.; Ahmed, J.; Krishnaiah, K.

Activated carbon is produced from coconut shell char using steam or carbon dioxide as the reacting gas in a 100 mm diameter fluidized bed reactor. The effect of process parameters such as reaction time, fluidizing velocity, particle size, static bed height, temperature of activation, fluidizing medium, and solid raw material on activation is studied. The product is characterized by determination of iodine number and BET surface area. The product obtained in the fluidized bed reactor is much superior in quality to the activated carbons produced by conventional processes. Based on the experimental observations, the optimum values of process parameters aremore » identified.« less

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Study of wear performance of deep drawing tooling

NASA Astrophysics Data System (ADS)

Naranje, Vishal G.; Karthikeyan, Ram; Nair, Vipin

2017-09-01

One of the most common challenges for many of the mechanical engineers and also in the field of materials science is the issue of occurrences of wear of the material parts which is used in certain applications that involves such surface interactions. In this paper, wear behaviour of particular grade High Carbon High Chromium Steel and many most famously D2, H13, O1 known as the Viking steel has been studied, evaluated and analyzed under certain processing parameters such as speed, load, track diameter and time required for deep drawing process to know it’s the wear rate and coefficient of friction. Also, the significance of the processing parameters which is used for wear testing analysis is also examined.

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Assessment of parameter uncertainty in hydrological model using a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis method

NASA Astrophysics Data System (ADS)

Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming

2016-07-01

Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model's capability for simulating/predicting water resources.

Application of Twin Screw Extrusion in the Manufacture of Cocrystals, Part I: Four Case Studies

PubMed Central

Daurio, Dominick; Medina, Cesar; Saw, Robert; Nagapudi, Karthik; Alvarez-Núñez, Fernando

2011-01-01

The application of twin screw extrusion (TSE) as a scalable and green process for the manufacture of cocrystals was investigated. Four model cocrystal forming systems, Caffeine-Oxalic acid, Nicotinamide-trans cinnamic acid, Carbamazepine-Saccharin, and Theophylline-Citric acid, were selected for the study. The parameters of the extrusion process that influenced cocrystal formation were examined. TSE was found to be an effective method to make cocrystals for all four systems studied. It was demonstrated that temperature and extent of mixing in the extruder were the primary process parameters that influenced extent of conversion to the cocrystal in neat TSE experiments. In addition to neat extrusion, liquid-assisted TSE was also demonstrated for the first time as a viable process for making cocrystals. Notably, the use of catalytic amount of benign solvents led to a lowering of processing temperatures required to form the cocrystal in the extruder. TSE should be considered as an efficient, scalable, and environmentally friendly process for the manufacture of cocrystals with little to no solvent requirements. PMID:24310598

Development of a copula-based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.

2017-06-01

In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas. Such a process can overcome both particle degeneration and sample impoverishment. The applicability of CopPF is illustrated with three case studies using a two-parameter simplified model and two conceptual hydrologic models. The results for the simplified model indicate that model parameters are highly correlated in the data assimilation process, suggesting a demand for full description of their dependence structure. Synthetic experiments on hydrologic data assimilation indicate that CopPF can rejuvenate particle evolution in large spaces and thus achieve good performances with low sample size scenarios. The applicability of CopPF is further illustrated through two real-case studies. It is shown that, compared with traditional particle filter (PF) and particle Markov chain Monte Carlo (PMCMC) approaches, the proposed method can provide more accurate results for both deterministic and probabilistic prediction with a sample size of 100. Furthermore, the sample size would not significantly influence the performance of CopPF. Also, the copula resampling approach dominates parameter evolution in CopPF, with more than 50% of particles sampled by copulas in most sample size scenarios.

A Module Experimental Process System Development Unit (MEPSDU)

NASA Technical Reports Server (NTRS)

1981-01-01

The purpose of this program is to demonstrate the technical readiness of a cost effective process sequence that has the potential for the production of flat plate photovoltaic modules which met the price goal in 1986 of $.70 or less per watt peak. Program efforts included: preliminary design review, preliminary cell fabrication using the proposed process sequence, verification of sandblasting back cleanup, study of resist parameters, evaluation of pull strength of the proposed metallization, measurement of contact resistance of Electroless Ni contacts, optimization of process parameter, design of the MEPSDU module, identification and testing of insulator tapes, development of a lamination process sequence, identification, discussions, demonstrations and visits with candidate equipment vendors, evaluation of proposals for tabbing and stringing machine.

Electrochemical Behavior of Sulfur in Aqueous Alkaline Solutions

NASA Astrophysics Data System (ADS)

Mamyrbekova, Aigul; Mamitova, A. D.; Mamyrbekova, Aizhan

2018-03-01

The kinetics and mechanism of the electrode oxidation-reduction of sulfur on an electrically conductive sulfur-graphite electrode in an alkaline solution was studied by the potentiodynamic method. To examine the mechanism of electrode processes occurring during AC polarization on a sulfur-graphite electrode, the cyclic polarization in both directions and anodic polarization curves were recorded. The kinetic parameters: charge transfer coefficients (α), diffusion coefficients ( D), heterogeneous rate constants of electrode process ( k s), and effective activation energies of the process ( E a) were calculated from the results of polarization measurements. An analysis of the results and calculated kinetic parameters of electrode processes showed that discharge ionization of sulfur in alkaline solutions occurs as a sequence of two stages and is a quasireversible process.

Mechanical Properties of Aluminum-Based Dissimilar Alloy Joints by Power Beams, Arc and FSW Processes

NASA Astrophysics Data System (ADS)

Okubo, Michinori; Kon, Tomokuni; Abe, Nobuyuki

Dissimilar smart joints are useful. In this research, welded quality of dissimilar aluminum alloys of 3 mm thickness by various welding processes and process parameters have been investigated by hardness and tensile tests, and observation of imperfection and microstructure. Base metals used in this study are A1050-H24, A2017-T3, A5083-O, A6061-T6 and A7075-T651. Welding processes used are YAG laser beam, electron beam, metal inert gas arc, tungsten inert gas arc and friction stir welding. The properties of weld zones are affected by welding processes, welding parameters and combination of base metals. Properties of high strength aluminum alloy joints are improved by friction stir welding.

Defining process design space for monoclonal antibody cell culture.

PubMed

Abu-Absi, Susan Fugett; Yang, LiYing; Thompson, Patrick; Jiang, Canping; Kandula, Sunitha; Schilling, Bernhard; Shukla, Abhinav A

2010-08-15

The concept of design space has been taking root as a foundation of in-process control strategies for biopharmaceutical manufacturing processes. During mapping of the process design space, the multidimensional combination of operational variables is studied to quantify the impact on process performance in terms of productivity and product quality. An efficient methodology to map the design space for a monoclonal antibody cell culture process is described. A failure modes and effects analysis (FMEA) was used as the basis for the process characterization exercise. This was followed by an integrated study of the inoculum stage of the process which includes progressive shake flask and seed bioreactor steps. The operating conditions for the seed bioreactor were studied in an integrated fashion with the production bioreactor using a two stage design of experiments (DOE) methodology to enable optimization of operating conditions. A two level Resolution IV design was followed by a central composite design (CCD). These experiments enabled identification of the edge of failure and classification of the operational parameters as non-key, key or critical. In addition, the models generated from the data provide further insight into balancing productivity of the cell culture process with product quality considerations. Finally, process and product-related impurity clearance was evaluated by studies linking the upstream process with downstream purification. Production bioreactor parameters that directly influence antibody charge variants and glycosylation in CHO systems were identified.

Inverse modeling of geochemical and mechanical compaction in sedimentary basins

NASA Astrophysics Data System (ADS)

Colombo, Ivo; Porta, Giovanni Michele; Guadagnini, Alberto

2015-04-01

We study key phenomena driving the feedback between sediment compaction processes and fluid flow in stratified sedimentary basins formed through lithification of sand and clay sediments after deposition. Processes we consider are mechanic compaction of the host rock and the geochemical compaction due to quartz cementation in sandstones. Key objectives of our study include (i) the quantification of the influence of the uncertainty of the model input parameters on the model output and (ii) the application of an inverse modeling technique to field scale data. Proper accounting of the feedback between sediment compaction processes and fluid flow in the subsurface is key to quantify a wide set of environmentally and industrially relevant phenomena. These include, e.g., compaction-driven brine and/or saltwater flow at deep locations and its influence on (a) tracer concentrations observed in shallow sediments, (b) build up of fluid overpressure, (c) hydrocarbon generation and migration, (d) subsidence due to groundwater and/or hydrocarbons withdrawal, and (e) formation of ore deposits. Main processes driving the diagenesis of sediments after deposition are mechanical compaction due to overburden and precipitation/dissolution associated with reactive transport. The natural evolution of sedimentary basins is characterized by geological time scales, thus preventing direct and exhaustive measurement of the system dynamical changes. The outputs of compaction models are plagued by uncertainty because of the incomplete knowledge of the models and parameters governing diagenesis. Development of robust methodologies for inverse modeling and parameter estimation under uncertainty is therefore crucial to the quantification of natural compaction phenomena. We employ a numerical methodology based on three building blocks: (i) space-time discretization of the compaction process; (ii) representation of target output variables through a Polynomial Chaos Expansion (PCE); and (iii) model inversion (parameter estimation) within a maximum likelihood framework. In this context, the PCE-based surrogate model enables one to (i) minimize the computational cost associated with the (forward and inverse) modeling procedures leading to uncertainty quantification and parameter estimation, and (ii) compute the full set of Sobol indices quantifying the contribution of each uncertain parameter to the variability of target state variables. Results are illustrated through the simulation of one-dimensional test cases. The analyses focuses on the calibration of model parameters through literature field cases. The quality of parameter estimates is then analyzed as a function of number, type and location of data.

A review of pharmaceutical extrusion: critical process parameters and scaling-up.

PubMed

Thiry, J; Krier, F; Evrard, B

2015-02-01

Hot melt extrusion has been a widely used process in the pharmaceutical area for three decades. In this field, it is important to optimize the formulation in order to meet specific requirements. However, the process parameters of the extruder should be as much investigated as the formulation since they have a major impact on the final product characteristics. Moreover, a design space should be defined in order to obtain the expected product within the defined limits. This gives some freedom to operate as long as the processing parameters stay within the limits of the design space. Those limits can be investigated by varying randomly the process parameters but it is recommended to use design of experiments. An examination of the literature is reported in this review to summarize the impact of the variation of the process parameters on the final product properties. Indeed, the homogeneity of the mixing, the state of the drug (crystalline or amorphous), the dissolution rate, the residence time, can be influenced by variations in the process parameters. In particular, the impact of the following process parameters: temperature, screw design, screw speed and feeding, on the final product, has been reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.

A study of process parameters on workpiece anisotropy in the laser engineered net shaping (LENSTM) process

NASA Astrophysics Data System (ADS)

Chandra, Shubham; Rao, Balkrishna C.

2017-06-01

The process of laser engineered net shaping (LENSTM) is an additive manufacturing technique that employs the coaxial flow of metallic powders with a high-power laser to form a melt pool and the subsequent deposition of the specimen on a substrate. Although research done over the past decade on the LENSTM processing of alloys of steel, titanium, nickel and other metallic materials typically reports superior mechanical properties in as-deposited specimens, when compared to the bulk material, there is anisotropy in the mechanical properties of the melt deposit. The current study involves the development of a numerical model of the LENSTM process, using the principles of computational fluid dynamics (CFD), and the subsequent prediction of the volume fraction of equiaxed grains to predict process parameters required for the deposition of workpieces with isotropy in their properties. The numerical simulation is carried out on ANSYS-Fluent, whose data on thermal gradient are used to determine the volume fraction of the equiaxed grains present in the deposited specimen. This study has been validated against earlier efforts on the experimental studies of LENSTM for alloys of nickel. Besides being applicable to the wider family of metals and alloys, the results of this study will also facilitate effective process design to improve both product quality and productivity.

Skin texture parameters of the dorsal hand in evaluating skin aging in China.

PubMed

Gao, Qian; Hu, Li-Wen; Wang, Yang; Xu, Wen-Ying; Ouyang, Nan-Ning; Dong, Guo-Qing; Shi, Song-Tian; Liu, Yang

2011-11-01

There are various non-invasive methods in skin morphology for assessing skin aging. The use of digital photography will make it easier and more convenient. In this study, we explored some skin texture parameters for evaluating skin aging using digital image processing. Two hundred and twenty-eight subjects who lived in Sanya, China, were involved. Individual sun exposure history and other factors influencing skin aging were collected by a questionnaire. Meanwhile, we took photos of their dorsal hands. Skin images were graded according to the Beagley-Gibson system. These skin images were also processed using image analysis software. Five skin texture parameters, Angle Num., Angle Max., Angle Diff., Distance and Grids, were produced in reference to the Beagley-Gibson system. All texture parameters were significantly associated with the Beagley-Gibson score. Among the parameters, the distance between primary lines (Distance) and the value of angle formed by intersection textures (Angle Max., Angle Diff.) were positively associated with the Beagley-Gibson score. However, there was a negative correlation between the number of grids (Grids), the number of angle (Angle Num.) and the Beagley-Gibson score. These texture parameters were also correlated with factors influencing skin aging such as sun exposure, age, smoking, drinking and body mass index. In multivariate analysis, Grids and Distance were mainly affected by age. But Angle Max. and Angle Diff. were mainly affected by sun exposure. It seemed that the skin surface morphologic parameters presented in our study reflect skin aging changes to some extent and could be used to describe skin aging using digital image processing. © 2011 John Wiley & Sons A/S.

Validation study and routine control monitoring of moist heat sterilization procedures.

PubMed

Shintani, Hideharu

2012-06-01

The proposed approach to validation of steam sterilization in autoclaves follows the basic life cycle concepts applicable to all validation programs. Understand the function of sterilization process, develop and understand the cycles to carry out the process, and define a suitable test or series of tests to confirm that the function of the process is suitably ensured by the structure provided. Sterilization of product and components and parts that come in direct contact with sterilized product is the most critical of pharmaceutical processes. Consequently, this process requires a most rigorous and detailed approach to validation. An understanding of the process requires a basic understanding of microbial death, the parameters that facilitate that death, the accepted definition of sterility, and the relationship between the definition and sterilization parameters. Autoclaves and support systems need to be designed, installed, and qualified in a manner that ensures their continued reliability. Lastly, the test program must be complete and definitive. In this paper, in addition to validation study, documentation of IQ, OQ and PQ concretely were described.

Wolf Creek Research Basin Cold REgion Process Studies - 1992-2003

NASA Astrophysics Data System (ADS)

Janowicz, R.; Hedstrom, N.; Pomeroy, J.; Granger, R.; Carey, S.

2004-12-01

The development of hydrological models in northern regions are complicated by cold region processes. Sparse vegetation influences snowpack accumulation, redistribution and melt, frozen ground effects infiltration and runoff and cold soils in the summer effect evapotranspiration rates. Situated in the upper Yukon River watershed, the 195 km2 Wolf Creek Research Basin was instrumented in 1992 to calibrate hydrologic flow models, and has since evolved into a comprehensive study of cold region processes and linkages, contributing significantly to hydrological and climate change modelling. Studies include those of precipitation distribution, snowpack accumulation and redistribution, energy balance, snowmelt infiltration, and water balance. Studies of the spatial variability of hydrometeorological data demonstrate the importance of physical parameters on their distribution and control on runoff processes. Many studies have also identified the complex interaction of several of the physical parameters, including topography, vegetation and frozen ground (seasonal or permafrost) as important. They also show that there is a fundamental, underlying spatial structure to the watershed that must be adequately represented in parameterization schemes for scaling and watershed modelling. The specific results of numerous studies are presented.

Geophysical study of the structure and processes of the continental convergence zones: Alpine-Himalayan Belt

NASA Technical Reports Server (NTRS)

Toksoz, M. Nafi; Molnar, Peter

1988-01-01

Intracontinental deformation occurrence and the processes and physical parameters that control the rates and styles of deformation were examined. Studies addressing specific mechanical aspects of deformation were reviewed and the studies of deformation and of the structure of specific areas were studied considering the strength of the material and the gravitational effect.

Process Parameter Optimization for Wobbling Laser Spot Welding of Ti6Al4V Alloy

NASA Astrophysics Data System (ADS)

Vakili-Farahani, F.; Lungershausen, J.; Wasmer, K.

Laser beam welding (LBW) coupled with "wobble effect" (fast oscillation of the laser beam) is very promising for high precision micro-joining industry. For this process, similarly to the conventional LBW, the laser welding process parameters play a very significant role in determining the quality of a weld joint. Consequently, four process parameters (laser power, wobble frequency, number of rotations within a single laser pulse and focused position) and 5 responses (penetration, width, heat affected zone (HAZ), area of the fusion zone, area of HAZ and hardness) were investigated for spot welding of Ti6Al4V alloy (grade 5) using a design of experiments (DoE) approach. This paper presents experimental results showing the effects of variating the considered most important process parameters on the spot weld quality of Ti6Al4V alloy. Semi-empirical mathematical models were developed to correlate laser welding parameters to each of the measured weld responses. Adequacies of the models were then examined by various methods such as ANOVA. These models not only allows a better understanding of the wobble laser welding process and predict the process performance but also determines optimal process parameters. Therefore, optimal combination of process parameters was determined considering certain quality criteria set.

Part weight verification between simulation and experiment of plastic part in injection moulding process

NASA Astrophysics Data System (ADS)

Amran, M. A. M.; Idayu, N.; Faizal, K. M.; Sanusi, M.; Izamshah, R.; Shahir, M.

2016-11-01

In this study, the main objective is to determine the percentage difference of part weight between experimental and simulation work. The effect of process parameters on weight of plastic part is also investigated. The process parameters involved were mould temperature, melt temperature, injection time and cooling time. Autodesk Simulation Moldflow software was used to run the simulation of the plastic part. Taguchi method was selected as Design of Experiment to conduct the experiment. Then, the simulation result was validated with the experimental result. It was found that the minimum and maximum percentage of differential of part weight between simulation and experimental work are 0.35 % and 1.43 % respectively. In addition, the most significant parameter that affected part weight is the mould temperature, followed by melt temperature, injection time and cooling time.

Process modeling and parameter optimization using radial basis function neural network and genetic algorithm for laser welding of dissimilar materials

NASA Astrophysics Data System (ADS)

Ai, Yuewei; Shao, Xinyu; Jiang, Ping; Li, Peigen; Liu, Yang; Yue, Chen

2015-11-01

The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.

Optimization of processing parameters of amaranth grits before grinding into flour

NASA Astrophysics Data System (ADS)

Zharkova, I. M.; Safonova, Yu A.; Slepokurova, Yu I.

2018-05-01

There are the results of experimental studies about the influence of infrared treatment (IR processing) parameters of the amaranth grits before their grinding into flour on the composition and properties of the received product. Using the method called as regressionfactor analysis, the optimal conditions of the thermal processing to the amaranth grits were obtained: the belt speed of the conveyor – 0.049 m/s; temperature of amaranth grits in the tempering silo – 65.4 °C the thickness of the layer of amaranth grits on the belt is 3 - 5 mm and the lamp power is 69.2 kW/m2. The conducted researches confirmed that thermal effect to the amaranth grains in the IR setting allows getting flour with a smaller size of starch grains, with the increased water-holding ability, and with a changed value of its glycemic index. Mathematical processing of experimental data allowed establishing the dependence of the structural and technological characteristics of the amaranth flour on the IR processing parameters of amaranth grits. The obtained results are quite consistent with the experimental ones that proves the effectiveness of optimization based on mathematical planning of the experiment to determine the influence of heat treatment optimal parameters of the amaranth grits on the functional and technological properties of the flour received from it.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody–peptide fusion

PubMed Central

Goldrick, Stephen; Holmes, William; Bond, Nicholas J.; Lewis, Gareth; Kuiper, Marcel; Turner, Richard

2017-01-01

ABSTRACT Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody–peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high‐throughput (HT) micro‐bioreactor system (AmbrTM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on‐line and off‐line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale‐up. Biotechnol. Bioeng. 2017;114: 2222–2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. PMID:28500668

Case studies on the physical-chemical parameters' variation during three different purification approaches destined to treat wastewaters from food industry.

PubMed

Ghimpusan, Marieta; Nechifor, Gheorghe; Nechifor, Aurelia-Cristina; Dima, Stefan-Ovidiu; Passeri, Piero

2017-12-01

The paper presents a set of three interconnected case studies on the depuration of food processing wastewaters by using aeration & ozonation and two types of hollow-fiber membrane bioreactor (MBR) approaches. A secondary and more extensive objective derived from the first one is to draw a clearer, broader frame on the variation of physical-chemical parameters during the purification of wastewaters from food industry through different operating modes with the aim of improving the management of water purification process. Chemical oxygen demand (COD), pH, mixed liquor suspended solids (MLSS), total nitrogen, specific nitrogen (NH 4 + , NO 2 - , NO 3 - ) total phosphorous, and total surfactants were the measured parameters, and their influence was discussed in order to establish the best operating mode to achieve the purification performances. The integrated air-ozone aeration process applied in the second operating mode lead to a COD decrease by up to 90%, compared to only 75% obtained in a conventional biological activated sludge process. The combined purification process of MBR and ozonation produced an additional COD decrease of 10-15%, and made the Total Surfactants values to comply to the specific legislation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spray drying of budesonide, formoterol fumarate and their composites-II. Statistical factorial design and in vitro deposition properties.

PubMed

Tajber, L; Corrigan, O I; Healy, A M

2009-02-09

The aim of this study was to investigate the effect of changing spray drying parameters on the production of a budesonide/formoterol fumarate 100:6 (w/w) composite. The systems were spray dried as solutions from 95% ethanol/5% water (v/v) using a Büchi 191-Mini Spray Dryer. A 2(5-1) factorial design study was undertaken to assess the consequence of altering spray drying processing variables on particle characteristics. The processing parameters that were studied were inlet temperature, spray drier airflow rate, pump rate, aspirator setting and feed concentration. Each batch of the resulting powder was characterised in terms of thermal and micromeritic properties as well as an in vitro deposition by twin impinger analysis. Overall, the parameter that had the greatest influence on each response investigated was production yield - airflow (higher airflow giving greater yields), median particle size - airflow (higher airflow giving smaller particle sizes) and Carr's compressibility index - feed concentration (lower feed concentration giving smaller Carr's indices). A six- to seven-fold difference in respirable fraction can be observed by changing the spray drying process parameters. The co-spray dried composite system which displayed best in vitro deposition characteristics, showed a 2.6-fold increase in respirable fraction in the twin impinger experiments and better dose uniformity compared with the physical mix of micronised powders.

How certain are the process parameterizations in our models?

NASA Astrophysics Data System (ADS)

Gharari, Shervan; Hrachowitz, Markus; Fenicia, Fabrizio; Matgen, Patrick; Razavi, Saman; Savenije, Hubert; Gupta, Hoshin; Wheater, Howard

2016-04-01

Environmental models are abstract simplifications of real systems. As a result, the elements of these models, including system architecture (structure), process parameterization and parameters inherit a high level of approximation and simplification. In a conventional model building exercise the parameter values are the only elements of a model which can vary while the rest of the modeling elements are often fixed a priori and therefore not subjected to change. Once chosen the process parametrization and model structure usually remains the same throughout the modeling process. The only flexibility comes from the changing parameter values, thereby enabling these models to reproduce the desired observation. This part of modeling practice, parameter identification and uncertainty, has attracted a significant attention in the literature during the last years. However what remains unexplored in our point of view is to what extent the process parameterization and system architecture (model structure) can support each other. In other words "Does a specific form of process parameterization emerge for a specific model given its system architecture and data while no or little assumption has been made about the process parameterization itself? In this study we relax the assumption regarding a specific pre-determined form for the process parameterizations of a rainfall/runoff model and examine how varying the complexity of the system architecture can lead to different or possibly contradictory parameterization forms than what would have been decided otherwise. This comparison implicitly and explicitly provides us with an assessment of how uncertain is our perception of model process parameterization in respect to the extent the data can support.

A novel process for production of spherical PBT powders and their processing behavior during laser beam melting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, Jochen, E-mail: jochen.schmidt@fau.de; Sachs, Marius; Fanselow, Stephanie

2016-03-09

Additive manufacturing processes like laser beam melting of polymers are established for production of prototypes and individualized parts. The transfer to other areas of application and to serial production is currently hindered by the limited availability of polymer powders with good processability. Within this contribution a novel process route for the production of spherical polymer micron-sized particles of good flowability has been established and applied to produce polybutylene terephthalate (PBT) powders. Moreover, the applicability of the PBT powders in selective laser beam melting and the dependencies of process parameters on device properties will be outlined. First, polymer micro particles aremore » produced by a novel wet grinding method. To improve the flowability the produced particles the particle shape is optimized by rounding in a heated downer reactor. A further improvement of flowability of the cohesive spherical PBT particles is realized by dry coating. An improvement of flowability by a factor of about 5 is achieved by subsequent rounding of the comminution product and dry-coating as proven by tensile strength measurements of the powders. The produced PBT powders were characterized with respect to their processability. Therefore thermal, rheological, optical and bulk properties were analyzed. Based on these investigations a range of processing parameters was derived. Parameter studies on thin layers, produced in a selective laser melting system, were conducted. Hence appropriate parameters for processing the PBT powders by laser beam melting, like building chamber temperature, scan speed and laser power have been identified.« less

Application of Fourier transform near-infrared spectroscopy to optimization of green tea steaming process conditions.

PubMed

Ono, Daiki; Bamba, Takeshi; Oku, Yuichi; Yonetani, Tsutomu; Fukusaki, Eiichiro

2011-09-01

In this study, we constructed prediction models by metabolic fingerprinting of fresh green tea leaves using Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression analysis to objectively optimize of the steaming process conditions in green tea manufacture. The steaming process is the most important step for manufacturing high quality green tea products. However, the parameter setting of the steamer is currently determined subjectively by the manufacturer. Therefore, a simple and robust system that can be used to objectively set the steaming process parameters is necessary. We focused on FT-NIR spectroscopy because of its simple operation, quick measurement, and low running costs. After removal of noise in the spectral data by principal component analysis (PCA), PLS regression analysis was performed using spectral information as independent variables, and the steaming parameters set by experienced manufacturers as dependent variables. The prediction models were successfully constructed with satisfactory accuracy. Moreover, the results of the demonstrated experiment suggested that the green tea steaming process parameters could be predicted on a larger manufacturing scale. This technique will contribute to improvement of the quality and productivity of green tea because it can objectively optimize the complicated green tea steaming process and will be suitable for practical use in green tea manufacture. Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Deploying response surface methodology (RSM) and glowworm swarm optimization (GSO) in optimizing warpage on a mobile phone cover

NASA Astrophysics Data System (ADS)

Lee, X. N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.; Shazzuan, S.

2017-09-01

Plastic injection moulding is a popular manufacturing method not only it is reliable, but also efficient and cost saving. It able to produce plastic part with detailed features and complex geometry. However, defects in injection moulding process degrades the quality and aesthetic of the injection moulded product. The most common defect occur in the process is warpage. Inappropriate process parameter setting of injection moulding machine is one of the reason that leads to the occurrence of warpage. The aims of this study were to improve the quality of injection moulded part by investigating the optimal parameters in minimizing warpage using Response Surface Methodology (RSM) and Glowworm Swarm Optimization (GSO). Subsequent to this, the most significant parameter was identified and recommended parameters setting was compared with the optimized parameter setting using RSM and GSO. In this research, the mobile phone case was selected as case study. The mould temperature, melt temperature, packing pressure, packing time and cooling time were selected as variables whereas warpage in y-direction was selected as responses in this research. The simulation was carried out by using Autodesk Moldflow Insight 2012. In addition, the RSM was performed by using Design Expert 7.0 whereas the GSO was utilized by using MATLAB. The warpage in y direction recommended by RSM were reduced by 70 %. The warpages recommended by GSO were decreased by 61 % in y direction. The resulting warpages under optimal parameter setting by RSM and GSO were validated by simulation in AMI 2012. RSM performed better than GSO in solving warpage issue.

A GUI-based Tool for Bridging the Gap between Models and Process-Oriented Studies

NASA Astrophysics Data System (ADS)

Kornfeld, A.; Van der Tol, C.; Berry, J. A.

2014-12-01

Models used for simulation of photosynthesis and transpiration by canopies of terrestrial plants typically have subroutines such as STOMATA.F90, PHOSIB.F90 or BIOCHEM.m that solve for photosynthesis and associated processes. Key parameters such as the Vmax for Rubisco and temperature response parameters are required by these subroutines. These are often taken from the literature or determined by separate analysis of gas exchange experiments. It is useful to note however that subroutines can be extracted and run as standalone models to simulate leaf responses collected in gas exchange experiments. Furthermore, there are excellent non-linear fitting tools that can be used to optimize the parameter values in these models to fit the observations. Ideally the Vmax fit in this way should be the same as that determined by a separate analysis, but it may not because of interactions with other kinetic constants and the temperature dependence of these in the full subroutine. We submit that it is more useful to fit the complete model to the calibration experiments rather as disaggregated constants. We designed a graphical user interface (GUI) based tool that uses gas exchange photosynthesis data to directly estimate model parameters in the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model and, at the same time, allow researchers to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. We have also ported some of this functionality to an Excel spreadsheet, which could be used as a teaching tool to help integrate process-oriented and model-oriented studies.

Changes in water quality parameters due to in-sewer processes.

PubMed

Boxall, J; Shepherd, W; Guymer, I; Fox, K

2003-01-01

Combined sewer systems contain a large number of organic and inorganic pollutants from both domestic and industrial sources. These pollutants are often retained within the combined sewer system for significant lengths of time before entering sewage treatment works, or being spilt to a watercourse via a combined sewer overflow (CSO) during storm conditions. Currently little knowledge exists concerning the effects of in sewer processes on pollutants. Understanding of in-sewer processes is important for the effective and efficient design of treatment works and CSO chambers and for impact assessments on receiving waters. A series of studies covering storm and dry weather flow conditions were undertaken with the aim of investigating the nature of in-sewer processes. These studies consisted of marking a body of water with a fluorescent tracer. The tracer was then monitored at a series of downstream sites, and discrete samples collected from the body of water as it progressed through the sewer. The samples were analysed for water quality parameters and these results investigated in tandem with the detailed hydraulic information gained through the tracer studies. The results highlight the hydraulic differences between storm and dry weather conditions such as increased travel times and mixing under storm conditions. The Advection Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) model parameters have been quantified for the tracer data. The ADE mixing coefficient is shown to increase by an order of magnitude for storm conditions. The ADZ dispersive fraction parameter is shown to be approximately constant with flow. Chemical reactions and decay within the sewer system were found to be consistent with oxygen limitation.

Commercialization of the Conversion of Bagasse to Ethanol. Summary quarterly report for the period January-September 1999

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2000-02-01

These studies were intended to further refine sugar yield parameters which effect sugar yield such as feedstock particle size, debris, acid soak time, temperature, dewatering, and pretreatment conditions (such as temperature, reaction time, percentage solids concentration, acid concentration), liquid-solids separation, and detoxification parameters (such as time temperature and mixing of detoxification ingredients). Validate and refine parameters, which affect ethanol yield such as detoxification conditions mentioned above, and to fermenter conditions such as temperature, pH adjustment, aeration, nutrients, and charging sequence. Materials of construction will be evaluated also. Evaluate stillage to determine clarification process and suitability for recycle; evaluate lignocellulosic cakemore » for thermal energy recovery to produce heat and electricity for the process; and Support Studies at UF - Toxin Amelioration and Fermentation; TVA work will provide pre-hydroylsates for the evaluation of BCI proprietary methods of toxin amelioration. Pre-hydrolysates from batch studies will allow the determination of the range of allowable hydrolyze conditions that can be used to produce a fermentable sugar stream. This information is essential to guide selection of process parameters for refinement and validation in the continuous pretreatment reactor, and for overall process design. Additional work will be conducted at UFRFI to develop improved strains that are resistant to inhibitors. The authors are quite optimistic about the long-term prospects for this advancement having recently developed strains with a 25%--50% increase in ethanol production. The biocatalyst platform selected originally, genetically engineered Escherichia coli B, has proven to be quite robust and adaptable.« less

Friction Stir Welding in Wrought and Cast Aluminum Alloys: Weld Quality Evaluation and Effects of Processing Parameters on Microstructure and Mechanical Properties

NASA Astrophysics Data System (ADS)

Pan, Yi; Lados, Diana A.

2017-04-01

Friction stir welding (FSW) is a solid-state process widely used for joining similar and dissimilar materials for critical applications in the transportation sector. Understanding the effects of the process on microstructure and mechanical properties is critical in design for structural integrity. In this study, four aluminum alloy systems (wrought 6061-T651 and cast A356, 319, and A390) were processed in both as-fabricated and pre-weld heat-treated (T6) conditions using various processing parameters. The effects of processing and heat treatment on the resulting microstructures, macro-/micro-hardness, and tensile properties were systematically investigated and mechanistically correlated to changes in grain size, characteristic phases, and strengthening precipitates. Tensile tests were performed at room temperature both along and across the welding zones. A new method able to evaluate weld quality (using a weld quality index) was developed based on the stress concentration calculated under tensile loading. Optimum processing parameter domains that provide both defect-free welds and good mechanical properties were determined for each alloy and associated with the thermal history of the process. These results were further related to characteristic microstructural features, which can be used for component design and materials/process optimization.

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

Unraveling the Processing Parameters in Friction Stir Welding

NASA Technical Reports Server (NTRS)

Schneider, Judy; Nunes, Arthur C., Jr.

2005-01-01

In friction stir welding (FSW), a rotating threaded pin tool is translated along a weld seam, literally stirring the edges of the seam together. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path or paths is required. In this study, various markers are used to trace the flow paths of the metal. X-ray radiographs record the segmentation and position of the wire. Several variations in the trajectories can be differentiated within the weld zone.

Effect of Electron Beam Freeform Fabrication (EBF3) Processing Parameters on Composition of Ti-6-4

NASA Technical Reports Server (NTRS)

Lach, Cynthia L.; Taminger, Karen; Schuszler, A. Bud, II; Sankaran, Sankara; Ehlers, Helen; Nasserrafi, Rahbar; Woods, Bryan

2007-01-01

The Electron Beam Freeform Fabrication (EBF3) process developed at NASA Langley Research Center was evaluated using a design of experiments approach to determine the effect of processing parameters on the composition and geometry of Ti-6-4 deposits. The effects of three processing parameters: beam power, translation speed, and wire feed rate, were investigated by varying one while keeping the remaining parameters constant. A three-factorial, three-level, fully balanced mutually orthogonal array (L27) design of experiments approach was used to examine the effects of low, medium, and high settings for the processing parameters on the chemistry, geometry, and quality of the resulting deposits. Single bead high deposits were fabricated and evaluated for 27 experimental conditions. Loss of aluminum in Ti-6-4 was observed in EBF3 processing due to selective vaporization of the aluminum from the sustained molten pool in the vacuum environment; therefore, the chemistries of the deposits were measured and compared with the composition of the initial wire and base plate to determine if the loss of aluminum could be minimized through careful selection of processing parameters. The influence of processing parameters and coupling between these parameters on bulk composition, measured by Direct Current Plasma (DCP), local microchemistries determined by Wavelength Dispersive Spectrometry (WDS), and deposit geometry will also be discussed.

Machining of bone: Analysis of cutting force and surface roughness by turning process.

PubMed

Noordin, M Y; Jiawkok, N; Ndaruhadi, P Y M W; Kurniawan, D

2015-11-01

There are millions of orthopedic surgeries and dental implantation procedures performed every year globally. Most of them involve machining of bones and cartilage. However, theoretical and analytical study on bone machining is lagging behind its practice and implementation. This study views bone machining as a machining process with bovine bone as the workpiece material. Turning process which makes the basis of the actually used drilling process was experimented. The focus is on evaluating the effects of three machining parameters, that is, cutting speed, feed, and depth of cut, to machining responses, that is, cutting forces and surface roughness resulted by the turning process. Response surface methodology was used to quantify the relation between the machining parameters and the machining responses. The turning process was done at various cutting speeds (29-156 m/min), depths of cut (0.03 -0.37 mm), and feeds (0.023-0.11 mm/rev). Empirical models of the resulted cutting force and surface roughness as the functions of cutting speed, depth of cut, and feed were developed. Observation using the developed empirical models found that within the range of machining parameters evaluated, the most influential machining parameter to the cutting force is depth of cut, followed by feed and cutting speed. The lowest cutting force was obtained at the lowest cutting speed, lowest depth of cut, and highest feed setting. For surface roughness, feed is the most significant machining condition, followed by cutting speed, and with depth of cut showed no effect. The finest surface finish was obtained at the lowest cutting speed and feed setting. © IMechE 2015.

Impact Of The Material Variability On The Stamping Process: Numerical And Analytical Analysis

NASA Astrophysics Data System (ADS)

Ledoux, Yann; Sergent, Alain; Arrieux, Robert

2007-05-01

The finite element simulation is a very useful tool in the deep drawing industry. It is used more particularly for the development and the validation of new stamping tools. It allows to decrease cost and time for the tooling design and set up. But one of the most important difficulties to have a good agreement between the simulation and the real process comes from the definition of the numerical conditions (mesh, punch travel speed, limit conditions,…) and the parameters which model the material behavior. Indeed, in press shop, when the sheet set changes, often a variation of the formed part geometry is observed according to the variability of the material properties between these different sets. This last parameter represents probably one of the main source of process deviation when the process is set up. That's why it is important to study the influence of material data variation on the geometry of a classical stamped part. The chosen geometry is an omega shaped part because of its simplicity and it is representative one in the automotive industry (car body reinforcement). Moreover, it shows important springback deviations. An isotropic behaviour law is assumed. The impact of the statistical deviation of the three law coefficients characterizing the material and the friction coefficient around their nominal values is tested. A Gaussian distribution is supposed and their impact on the geometry variation is studied by FE simulation. An other approach is envisaged consisting in modeling the process variability by a mathematical model and then, in function of the input parameters variability, it is proposed to define an analytical model which leads to find the part geometry variability around the nominal shape. These two approaches allow to predict the process capability as a function of the material parameter variability.

Design and performance study of an orthopaedic surgery robotized module for automatic bone drilling.

PubMed

Boiadjiev, George; Kastelov, Rumen; Boiadjiev, Tony; Kotev, Vladimir; Delchev, Kamen; Zagurski, Kazimir; Vitkov, Vladimir

2013-12-01

Many orthopaedic operations involve drilling and tapping before the insertion of screws into a bone. This drilling is usually performed manually, thus introducing many problems. These include attaining a specific drilling accuracy, preventing blood vessels from breaking, and minimizing drill oscillations that would widen the hole. Bone overheating is the most important problem. To avoid such problems and reduce the subjective factor, automated drilling is recommended. Because numerous parameters influence the drilling process, this study examined some experimental methods. These concerned the experimental identification of technical drilling parameters, including the bone resistance force and temperature in the drilling process. During the drilling process, the following parameters were monitored: time, linear velocity, angular velocity, resistance force, penetration depth, and temperature. Specific drilling effects were revealed during the experiments. The accuracy was improved at the starting point of the drilling, and the error for the entire process was less than 0.2 mm. The temperature deviations were kept within tolerable limits. The results of various experiments with different drilling velocities, drill bit diameters, and penetration depths are presented in tables, as well as the curves of the resistance force and temperature with respect to time. Real-time digital indications of the progress of the drilling process are shown. Automatic bone drilling could entirely solve the problems that usually arise during manual drilling. An experimental setup was designed to identify bone drilling parameters such as the resistance force arising from variable bone density, appropriate mechanical drilling torque, linear speed of the drill, and electromechanical characteristics of the motors, drives, and corresponding controllers. Automatic drilling guarantees greater safety for the patient. Moreover, the robot presented is user-friendly because it is simple to set robot tasks, and process data are collected in real time. Copyright © 2013 John Wiley & Sons, Ltd.

Welding of Al6061and Al6082-Cu composite by friction stir processing

NASA Astrophysics Data System (ADS)

Iyer, R. B.; Dhabale, R. B.; Jatti, V. S.

2016-09-01

Present study aims at investigating the influence of process parameters on the microstructure and mechanical properties such as tensile strength and hardness of the dissimilar metal without and with copper powder. Before conducting the copper powder experiments, optimum process parameters were obtained by conducting experiments without copper powder. Taguchi's experimental L9 orthogonal design layout was used to carry out the experiments without copper powder. Threaded pin tool geometry was used for conducting the experiments. Based on the experimental results and Taguchi's analysis it was found that maximum tensile strength of 66.06 MPa was obtained at 1400 rpm spindle speed and weld speed of 20 mm/min. Maximum micro hardness (92 HV) was obtained at 1400 rpm spindle speed and weld speed of 16 mm/min. At these optimal setting of process parameters aluminium alloys were welded with the copper powder. Experimental results demonstrated that the tensile strength (96.54 MPa) and micro hardness (105 HV) of FSW was notably affected by the addition of copper powder when compared with FSW joint without copper powder. Tensile failure specimen was analysed using Scanning Electron Microscopy in order to study the failure mechanism.

The effect of pelleting on in situ rumen degradability of compound feed containing brown rice for dairy cows.

PubMed

Tagawa, Shin-Ichi; Yoshida, Norio; Iino, Yukihiro; Horiguchi, Ken-Ichi; Takahashi, Toshiyoshi; Watanabe, Maria; Takemura, Kei; Ito, Syuhei; Mikami, Toyoji

2017-01-01

This study was conducted to determine the effect of pelleting on in situ dry matter degradability of pelleted compound feed containing brown rice for dairy cows. Mash feed of the same composition was used as a control and the in situ study was conducted using three non-lactating Holstein steers fitted with a rumen cannula. The feeds contained 32.3% brown rice, 19.4% rapeseed meal, 11.4% wheat bran and 10.6% soybean meal (fresh weight basis). Except for moisture content, the chemical composition of the feed was not affected by pelleting. In situ dry matter disappearance of the feed increased from 0 to 2 h and after 72 h of incubation with pellet processing. Integration of the dry matter disappearance values over time revealed that degradability parameter a (soluble fraction) increased with pellet processing, whereas parameter b (potentially degradable fraction) decreased. Parameter c (fractional rate of degradation) and effective degradability (5% passage rate) were not affected by pellet processing. We concluded that pellet processing promotes rumen degradability at early incubation hours when the pelleted feed contains brown rice. © 2016 Japanese Society of Animal Science.

The impact of semen processing on sperm parameters and pregnancy rates after intrauterine insemination.

PubMed

Ruiter-Ligeti, Jacob; Agbo, Chioma; Dahan, Michael

2017-06-01

The objective of this retrospective study was to evaluate the effect of semen processing on computer analyzed semen parameters and pregnancy rates after intrauterine insemination (IUI). Over a two-year period, a total of 981 couples undergoing 2231 IUI cycles were evaluated and the freshly collected non-donor semen was analyzed before and after density gradient centrifugation (DGC). DGC led to significant increases in sperm concentration by 66±74 ×106/mL (P=0.0001), percentage of motile sperm by 24±22% (P=0.0001), concentration motile by 27±58 ×106/mL (P=0.0001), and forward sperm progression by 18±14 µ/s (P=0.0001). In 95% of cases, there was a decrease in the total motile sperm count (TMSC), with an average decrease of 50±124% compared to pre-processed samples (P=0.0001). Importantly, the decrease in TMSC did not negatively affect pregnancy rates (P=0.45). This study proves that DGC leads to significant increases in most sperm parameters, with the exception of TMSC. Remarkably, the decrease in TMSC did not affect the pregnancy rate. This should reassure clinicians when the TMSC is negatively affected by processing.

Impregnation of Composite Materials: a Numerical Study

NASA Astrophysics Data System (ADS)

Baché, Elliott; Dupleix-Couderc, Chloé; Arquis, Eric; Berdoyes, Isabelle

2017-12-01

Oxide ceramic matrix composites are currently being developed for aerospace applications such as the exhaust, where the parts are subject to moderately high temperatures (≈ 700 ∘C) and oxidation. These composite materials are normally formed by, among other steps, impregnating a ceramic fabric with a slurry of ceramic particles. This impregnation process can be complex, with voids possibly forming in the fabric depending on the process parameters and material properties. Unwanted voids or macroporosity within the fabric can decrease the mechanical properties of the parts. In order to design an efficient manufacturing process able to impregnate the fabric well, numerical simulations may be used to design the process as well as the slurry. In this context, a tool is created for modeling different processes. Thétis, which solves the Navier-Stokes-Darcy-Brinkman equation using finite volumes, is expanded to take into account capillary pressures on the mesoscale. This formulation allows for more representativity than for Darcy's law (homogeneous preform) simulations while avoiding the prohibitive simulation times of a full discretization for the composing fibers at the representative elementary volume scale. The resulting tool is first used to investigate the effect of varying the slurry parameters on impregnation evolution. Two different processes, open bath impregnation and wet lay-up, are then studied with emphasis on varying their input parameters (e.g. inlet velocity).

Diamond Deposition and Defect Chemistry Studied via Solid State NMR

DTIC Science & Technology

1994-06-30

system can be found elsewhere (121. The flame characteristics depend on a number of parameters . The flame conditions depend on (a) equivalence ratio...b) pressure, (c) cold gas velocity, and (d) diluent. The effect of the various parameters are described briefly. This quantity describes the carbon...important parameter that must be controlled carefully. Many chemical processes in flames, including those in which collision activation or stabilization

The Role of Parvalbumin, Sarcoplasmatic Reticulum Calcium Pump Rate, Rates of Cross-Bridge Dynamics, and Ryanodine Receptor Calcium Current on Peripheral Muscle Fatigue: A Simulation Study

PubMed Central

Neumann, Verena

2016-01-01

A biophysical model of the excitation-contraction pathway, which has previously been validated for slow-twitch and fast-twitch skeletal muscles, is employed to investigate key biophysical processes leading to peripheral muscle fatigue. Special emphasis hereby is on investigating how the model's original parameter sets can be interpolated such that realistic behaviour with respect to contraction time and fatigue progression can be obtained for a continuous distribution of the model's parameters across the muscle units, as found for the functional properties of muscles. The parameters are divided into 5 groups describing (i) the sarcoplasmatic reticulum calcium pump rate, (ii) the cross-bridge dynamics rates, (iii) the ryanodine receptor calcium current, (iv) the rates of binding of magnesium and calcium ions to parvalbumin and corresponding dissociations, and (v) the remaining processes. The simulations reveal that the first two parameter groups are sensitive to contraction time but not fatigue, the third parameter group affects both considered properties, and the fourth parameter group is only sensitive to fatigue progression. Hence, within the scope of the underlying model, further experimental studies should investigate parvalbumin dynamics and the ryanodine receptor calcium current to enhance the understanding of peripheral muscle fatigue. PMID:27980606

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

The effect of spraying parameters on micro-structural properties of WC-12%Co coating deposited on copper substrate by HVOF process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sathwara, Nishit, E-mail: nishit-25@live.in; Metallurgical & Materials Engineering Department, Indus University, Ahmedabad-382115; Jariwala, C., E-mail: chetanjari@yahoo.com

High Velocity Oxy-Fuel (HVOF) thermal sprayed coatingmade from Tungsten Carbide (WC) isconsidered as one of the most durable materials as wear resistance for industrial applications at room temperature. WC coating offers high wear resistance due to its high hardness and tough matrix imparts. The coating properties strongly depend on thermal spray processing parameters, surface preparation and surface finish. In this investigation, the effect of variousHVOF process parameters was studied on WC coating properties. The WC-12%Co coating was produced on Copper substrate. Prior to coating, theCopper substrate surface was prepared by grit blasting. WC-12%Co coatings were deposited on Coppersubstrates with varyingmore » process parameters such as Oxygen gas pressure, Air pressure, and spraying distance. Microstructure of coating was examined using Scanning Electron Microscope (SEM) and characterization of phasespresentin the coating was examined by X-Ray Diffraction (XRD). Microhardness of all coatingswas measured by VickerMicrohardness tester. At low Oxygen Pressure(10.00 bar), high Air pressure (7bar) and short nozzle to substrate distance of 170mm, best coating adhesion and porosity less structure isachieved on Coppersubstrate.« less

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm

PubMed Central

Tamjidy, Mehran; Baharudin, B. T. Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-01-01

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon’s entropy. PMID:28772893

The effect of spraying parameters on micro-structural properties of WC-12%Co coating deposited on copper substrate by HVOF process

NASA Astrophysics Data System (ADS)

Sathwara, Nishit; Jariwala, C.; Chauhan, N.; Raole, P. M.; Basa, D. K.

2015-08-01

High Velocity Oxy-Fuel (HVOF) thermal sprayed coatingmade from Tungsten Carbide (WC) isconsidered as one of the most durable materials as wear resistance for industrial applications at room temperature. WC coating offers high wear resistance due to its high hardness and tough matrix imparts. The coating properties strongly depend on thermal spray processing parameters, surface preparation and surface finish. In this investigation, the effect of variousHVOF process parameters was studied on WC coating properties. The WC-12%Co coating was produced on Copper substrate. Prior to coating, theCopper substrate surface was prepared by grit blasting. WC-12%Co coatings were deposited on Coppersubstrates with varying process parameters such as Oxygen gas pressure, Air pressure, and spraying distance. Microstructure of coating was examined using Scanning Electron Microscope (SEM) and characterization of phasespresentin the coating was examined by X-Ray Diffraction (XRD). Microhardness of all coatingswas measured by VickerMicrohardness tester. At low Oxygen Pressure(10.00 bar), high Air pressure (7bar) and short nozzle to substrate distance of 170mm, best coating adhesion and porosity less structure isachieved on Coppersubstrate.

Performance Assessment Uncertainty Analysis for Japan's HLW Program Feasibility Study (H12)

DOE Office of Scientific and Technical Information (OSTI.GOV)

BABA,T.; ISHIGURO,K.; ISHIHARA,Y.

1999-08-30

Most HLW programs in the world recognize that any estimate of long-term radiological performance must be couched in terms of the uncertainties derived from natural variation, changes through time and lack of knowledge about the essential processes. The Japan Nuclear Cycle Development Institute followed a relatively standard procedure to address two major categories of uncertainty. First, a FEatures, Events and Processes (FEPs) listing, screening and grouping activity was pursued in order to define the range of uncertainty in system processes as well as possible variations in engineering design. A reference and many alternative cases representing various groups of FEPs weremore » defined and individual numerical simulations performed for each to quantify the range of conceptual uncertainty. Second, parameter distributions were developed for the reference case to represent the uncertainty in the strength of these processes, the sequencing of activities and geometric variations. Both point estimates using high and low values for individual parameters as well as a probabilistic analysis were performed to estimate parameter uncertainty. A brief description of the conceptual model uncertainty analysis is presented. This paper focuses on presenting the details of the probabilistic parameter uncertainty assessment.« less

PERIOD ESTIMATION FOR SPARSELY SAMPLED QUASI-PERIODIC LIGHT CURVES APPLIED TO MIRAS

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Shiyuan; Huang, Jianhua Z.; Long, James

2016-12-01

We develop a nonlinear semi-parametric Gaussian process model to estimate periods of Miras with sparsely sampled light curves. The model uses a sinusoidal basis for the periodic variation and a Gaussian process for the stochastic changes. We use maximum likelihood to estimate the period and the parameters of the Gaussian process, while integrating out the effects of other nuisance parameters in the model with respect to a suitable prior distribution obtained from earlier studies. Since the likelihood is highly multimodal for period, we implement a hybrid method that applies the quasi-Newton algorithm for Gaussian process parameters and search the period/frequencymore » parameter space over a dense grid. A large-scale, high-fidelity simulation is conducted to mimic the sampling quality of Mira light curves obtained by the M33 Synoptic Stellar Survey. The simulated data set is publicly available and can serve as a testbed for future evaluation of different period estimation methods. The semi-parametric model outperforms an existing algorithm on this simulated test data set as measured by period recovery rate and quality of the resulting period–luminosity relations.« less

Multi-Objective Optimization of Friction Stir Welding Process Parameters of AA6061-T6 and AA7075-T6 Using a Biogeography Based Optimization Algorithm.

PubMed

Tamjidy, Mehran; Baharudin, B T Hang Tuah; Paslar, Shahla; Matori, Khamirul Amin; Sulaiman, Shamsuddin; Fadaeifard, Firouz

2017-05-15

The development of Friction Stir Welding (FSW) has provided an alternative approach for producing high-quality welds, in a fast and reliable manner. This study focuses on the mechanical properties of the dissimilar friction stir welding of AA6061-T6 and AA7075-T6 aluminum alloys. The FSW process parameters such as tool rotational speed, tool traverse speed, tilt angle, and tool offset influence the mechanical properties of the friction stir welded joints significantly. A mathematical regression model is developed to determine the empirical relationship between the FSW process parameters and mechanical properties, and the results are validated. In order to obtain the optimal values of process parameters that simultaneously optimize the ultimate tensile strength, elongation, and minimum hardness in the heat affected zone (HAZ), a metaheuristic, multi objective algorithm based on biogeography based optimization is proposed. The Pareto optimal frontiers for triple and dual objective functions are obtained and the best optimal solution is selected through using two different decision making techniques, technique for order of preference by similarity to ideal solution (TOPSIS) and Shannon's entropy.

Pearson's Functions to Describe FSW Weld Geometry

NASA Astrophysics Data System (ADS)

Lacombe, D.; Gutierrez-Orrantia, M. E.; Coupard, D.; Tcherniaeff, S.; Girot, F.

2011-01-01

Friction stir welding (FSW) is a relatively new joining technique particularly for aluminium alloys that are difficult to fusion weld. In this study, the geometry of the weld has been investigated and modelled using Pearson's functions. It has been demonstrated that the Pearson's parameters (mean, standard deviation, skewness, kurtosis and geometric constant) can be used to characterize the weld geometry and the tensile strength of the weld assembly. Pearson's parameters and process parameters are strongly correlated allowing to define a control process procedure for FSW assemblies which make radiographic or ultrasonic controls unnecessary. Finally, an optimisation using a Generalized Gradient Method allows to determine the geometry of the weld which maximises the assembly tensile strength.

Application of a data assimilation method via an ensemble Kalman filter to reactive urea hydrolysis transport modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juxiu Tong; Bill X. Hu; Hai Huang

2014-03-01

With growing importance of water resources in the world, remediations of anthropogenic contaminations due to reactive solute transport become even more important. A good understanding of reactive rate parameters such as kinetic parameters is the key to accurately predicting reactive solute transport processes and designing corresponding remediation schemes. For modeling reactive solute transport, it is very difficult to estimate chemical reaction rate parameters due to complex processes of chemical reactions and limited available data. To find a method to get the reactive rate parameters for the reactive urea hydrolysis transport modeling and obtain more accurate prediction for the chemical concentrations,more » we developed a data assimilation method based on an ensemble Kalman filter (EnKF) method to calibrate reactive rate parameters for modeling urea hydrolysis transport in a synthetic one-dimensional column at laboratory scale and to update modeling prediction. We applied a constrained EnKF method to pose constraints to the updated reactive rate parameters and the predicted solute concentrations based on their physical meanings after the data assimilation calibration. From the study results we concluded that we could efficiently improve the chemical reactive rate parameters with the data assimilation method via the EnKF, and at the same time we could improve solute concentration prediction. The more data we assimilated, the more accurate the reactive rate parameters and concentration prediction. The filter divergence problem was also solved in this study.« less

A new algorithm for design, operation and cost assessment of struvite (MgNH4PO4) precipitation processes.

PubMed

Birnhack, Liat; Nir, Oded; Telzhenski, Marina; Lahav, Ori

2015-01-01

Deliberate struvite (MgNH4PO4) precipitation from wastewater streams has been the topic of extensive research in the last two decades and is expected to gather worldwide momentum in the near future as a P-reuse technique. A wide range of operational alternatives has been reported for struvite precipitation, including the application of various Mg(II) sources, two pH elevation techniques and several Mg:P ratios and pH values. The choice of each operational parameter within the struvite precipitation process affects process efficiency, the overall cost and also the choice of other operational parameters. Thus, a comprehensive simulation program that takes all these parameters into account is essential for process design. This paper introduces a systematic decision-supporting tool which accepts a wide range of possible operational parameters, including unconventional Mg(II) sources (i.e. seawater and seawater nanofiltration brines). The study is supplied with a free-of-charge computerized tool (http://tx.technion.ac.il/~agrengn/agr/Struvite_Program.zip) which links two computer platforms (Python and PHREEQC) for executing thermodynamic calculations according to predefined kinetic considerations. The model can be (inter alia) used for optimizing the struvite-fluidized bed reactor process operation with respect to P removal efficiency, struvite purity and economic feasibility of the chosen alternative. The paper describes the algorithm and its underlying assumptions, and shows results (i.e. effluent water quality, cost breakdown and P removal efficiency) of several case studies consisting of typical wastewaters treated at various operational conditions.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

One-step global parameter estimation of kinetic inactivation parameters for Bacillus sporothermodurans spores under static and dynamic thermal processes.

PubMed

Cattani, F; Dolan, K D; Oliveira, S D; Mishra, D K; Ferreira, C A S; Periago, P M; Aznar, A; Fernandez, P S; Valdramidis, V P

2016-11-01

Bacillus sporothermodurans produces highly heat-resistant endospores, that can survive under ultra-high temperature. High heat-resistant sporeforming bacteria are one of the main causes for spoilage and safety of low-acid foods. They can be used as indicators or surrogates to establish the minimum requirements for heat processes, but it is necessary to understand their thermal inactivation kinetics. The aim of the present work was to study the inactivation kinetics under both static and dynamic conditions in a vegetable soup. Ordinary least squares one-step regression and sequential procedures were applied for estimating these parameters. Results showed that multiple dynamic heating profiles, when analyzed simultaneously, can be used to accurately estimate the kinetic parameters while significantly reducing estimation errors and data collection. Copyright © 2016 Elsevier Ltd. All rights reserved.

Process characterization and Design Space definition.

PubMed

Hakemeyer, Christian; McKnight, Nathan; St John, Rick; Meier, Steven; Trexler-Schmidt, Melody; Kelley, Brian; Zettl, Frank; Puskeiler, Robert; Kleinjans, Annika; Lim, Fred; Wurth, Christine

2016-09-01

Quality by design (QbD) is a global regulatory initiative with the goal of enhancing pharmaceutical development through the proactive design of pharmaceutical manufacturing process and controls to consistently deliver the intended performance of the product. The principles of pharmaceutical development relevant to QbD are described in the ICH guidance documents (ICHQ8-11). An integrated set of risk assessments and their related elements developed at Roche/Genentech were designed to provide an overview of product and process knowledge for the production of a recombinant monoclonal antibody (MAb). This chapter describes the tools used for the characterization and validation of MAb manufacturing process under the QbD paradigm. This comprises risk assessments for the identification of potential Critical Process Parameters (pCPPs), statistically designed experimental studies as well as studies assessing the linkage of the unit operations. Outcome of the studies is the classification of process parameters according to their criticality and the definition of appropriate acceptable ranges of operation. The process and product knowledge gained in these studies can lead to the approval of a Design Space. Additionally, the information gained in these studies are used to define the 'impact' which the manufacturing process can have on the variability of the CQAs, which is used to define the testing and monitoring strategy. Copyright © 2016 International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Numerical Studies on the Failure Process of Heterogeneous Brittle Rocks or Rock-Like Materials under Uniaxial Compression

PubMed Central

Guo, Songfeng; Qi, Shengwen; Zou, Yu; Zheng, Bowen

2017-01-01

In rocks or rock-like materials, the constituents, e.g. quartz, calcite and biotite, as well as the microdefects have considerably different mechanical properties that make such materials heterogeneous at different degrees. The failure of materials subjected to external loads is a cracking process accompanied with stress redistribution due to material heterogeneity. However, the latter cannot be observed from the experiments in laboratory directly. In this study, the cracking and stress features during uniaxial compression process are numerically studied based on a presented approach. A plastic strain dependent strength model is implemented into the continuous numerical tool—Fast Lagrangian Analysis of Continua in three Dimensions (FLAC3D), and the Gaussian statistical function is adopted to depict the heterogeneity of mechanical parameters including elastic modulus, friction angle, cohesion and tensile strength. The mean parameter μ and the coefficient of variance (hcv, the ratio of mean parameter to standard deviation) in the function are used to define the mean value and heterogeneity degree of the parameters, respectively. The results show that this numerical approach can perfectly capture the general features of brittle materials including fracturing process, AE events as well as stress-strain curves. Furthermore, the local stress disturbance is analyzed and the crack initiation stress threshold is identified based on the AE events process and stress-strain curves. It is shown that the stress concentration always appears in the undamaged elements near the boundary of damaged sites. The peak stress and crack initiation stress are both heterogeneity dependent, i.e., a linear relation exists between the two stress thresholds and hcv. The range of hcv is suggested as 0.12 to 0.21 for most rocks. The stress concentration degree is represented by a stress concentration factor and found also heterogeneity dominant. Finally, it is found that there exists a consistent tendency between the local stress difference and the AE events process. PMID:28772738

Numerical Studies on the Failure Process of Heterogeneous Brittle Rocks or Rock-Like Materials under Uniaxial Compression.

PubMed

Guo, Songfeng; Qi, Shengwen; Zou, Yu; Zheng, Bowen

2017-04-01

In rocks or rock-like materials, the constituents, e.g. quartz, calcite and biotite, as well as the microdefects have considerably different mechanical properties that make such materials heterogeneous at different degrees. The failure of materials subjected to external loads is a cracking process accompanied with stress redistribution due to material heterogeneity. However, the latter cannot be observed from the experiments in laboratory directly. In this study, the cracking and stress features during uniaxial compression process are numerically studied based on a presented approach. A plastic strain dependent strength model is implemented into the continuous numerical tool-Fast Lagrangian Analysis of Continua in three Dimensions (FLAC 3D ), and the Gaussian statistical function is adopted to depict the heterogeneity of mechanical parameters including elastic modulus, friction angle, cohesion and tensile strength. The mean parameter μ and the coefficient of variance ( h cv , the ratio of mean parameter to standard deviation) in the function are used to define the mean value and heterogeneity degree of the parameters, respectively. The results show that this numerical approach can perfectly capture the general features of brittle materials including fracturing process, AE events as well as stress-strain curves. Furthermore, the local stress disturbance is analyzed and the crack initiation stress threshold is identified based on the AE events process and stress-strain curves. It is shown that the stress concentration always appears in the undamaged elements near the boundary of damaged sites. The peak stress and crack initiation stress are both heterogeneity dependent, i.e., a linear relation exists between the two stress thresholds and h cv . The range of h cv is suggested as 0.12 to 0.21 for most rocks. The stress concentration degree is represented by a stress concentration factor and found also heterogeneity dominant. Finally, it is found that there exists a consistent tendency between the local stress difference and the AE events process.

The effect of thermal processing on microstructure and mechanical properties in a nickel-iron alloy

NASA Astrophysics Data System (ADS)

Yang, Ling

The correlation between processing conditions, resulted microstructure and mechanical properties is of interest in the field of metallurgy for centuries. In this work, we investigated the effect of thermal processing parameters on microstructure, and key mechanical properties to turbine rotor design: tensile yield strength and crack growth resistance, for a nickel-iron based superalloy Inconel 706. The first step of the designing of experiments is to find parameter ranges for thermal processing. Physical metallurgy on superalloys was combined with finite element analysis to estimate variations in thermal histories for a large Alloy 706 forging, and the results were adopted for designing of experiments. Through the systematic study, correlation was found between the processing parameters and the microstructure. Five different types of grain boundaries were identified by optical metallography, fractography, and transmission electron microscopy, and they were found to be associated with eta precipitation at the grain boundaries. Proportions of types of boundaries, eta size, spacing and angle respect to the grain boundary were found to be dependent on processing parameters. Differences in grain interior precipitates were also identified, and correlated with processing conditions. Further, a strong correlation between microstructure and mechanical properties was identified. The grain boundary precipitates affect the time dependent crack propagation resistance, and different types of boundaries have different levels of resistance. Grain interior precipitates were correlated with tensile yield strength. It was also found that there is a strong environmental effect on time dependent crack propagation resistance, and the sensitivity to environmental damage is microstructure dependent. The microstructure with eta decorated on grain boundaries by controlled processing parameters is more resistant to environmental damage through oxygen embrittlement than material without eta phase on grain boundaries. Effort was made to explore the mechanisms of improving the time dependent crack propagation resistance through thermal processing, several mechanisms were identified in both environment dependent and environment independent category, and they were ranked based on their contributions in affecting crack propagation.

Boron-doped few-walled carbon nanotubes: novel synthesis and properties

NASA Astrophysics Data System (ADS)

Preston, Colin; Song, Da; Taillon, Josh; Cumings, John; Hu, Liangbing

2016-11-01

Few-walled carbon nanotubes offer a unique marriage of graphitic quality and robustness to ink-processing; however, doping procedures that may alter the band structure of these few-walled nanotubes are still lacking. This report introduces a novel solution-injected chemical vapor deposition growth process to fabricate the first boron-doped few-walled carbon nanotubes (B-FWNTs) reported in literature, which may have extensive applications in battery devices. A comprehensive characterization of the as-grown B-FWNTs confirms successful boron substitution in the graphitic lattice, and reveals varying growth parameters impact the structural properties of B-FWNT yield. An investigation into the optimal growth purification parameters and ink-making procedures was also conducted. This study introduces the first process technique to successfully grow intrinsically p-doped FWNTs, and provides the first investigation into the impact factors of the growth parameters, purification steps, and ink-making processes on the structural properties of the B-FWNTs and the electrical properties of the resulting spray-coated thin-film electrodes.

A primer of statistical methods for correlating parameters and properties of electrospun poly(L-lactide) scaffolds for tissue engineering--PART 1: design of experiments.

PubMed

Seyedmahmoud, Rasoul; Rainer, Alberto; Mozetic, Pamela; Maria Giannitelli, Sara; Trombetta, Marcella; Traversa, Enrico; Licoccia, Silvia; Rinaldi, Antonio

2015-01-01

Tissue engineering scaffolds produced by electrospinning are of enormous interest, but still lack a true understanding about the fundamental connection between the outstanding functional properties, the architecture, the mechanical properties, and the process parameters. Fragmentary results from several parametric studies only render some partial insights that are hard to compare and generally miss the role of parameters interactions. To bridge this gap, this article (Part-1 of 2) features a case study on poly-L-lactide scaffolds to demonstrate how statistical methods such as design of experiments can quantitatively identify the correlations existing between key scaffold properties and control parameters, in a systematic, consistent, and comprehensive manner disentangling main effects from interactions. The morphological properties (i.e., fiber distribution and porosity) and mechanical properties (Young's modulus) are "charted" as a function of molecular weight (MW) and other electrospinning process parameters (the Xs), considering the single effect as well as interactions between Xs. For the first time, the major role of the MW emerges clearly in controlling all scaffold properties. The correlation between mechanical and morphological properties is also addressed. © 2014 Wiley Periodicals, Inc.

An XRPD and EPR spectroscopy study of microcrystalline calcite bioprecipitated by Bacillus subtilis

NASA Astrophysics Data System (ADS)

Perito, B.; Romanelli, M.; Buccianti, A.; Passaponti, M.; Montegrossi, G.; Di Benedetto, F.

2018-05-01

We report in this study the first XRPD and EPR spectroscopy characterisation of a biogenic calcite, obtained from the activity of the bacterium Bacillus subtilis. Microcrystalline calcite powders obtained from bacterial culture in a suitable precipitation liquid medium were analysed without further manipulation. Both techniques reveal unusual parameters, closely related to the biological source of the mineral, i.e., to the bioprecipitation process and in particular to the organic matrix observed inside calcite. In detail, XRPD analysis revealed that bacterial calcite has slightly higher c/a lattice parameters ratio than abiotic calcite. This correlation was already noticed in microcrystalline calcite samples grown by bio-mineralisation processes, but it had never been previously verified for bacterial biocalcites. EPR spectroscopy evidenced an anomalously large value of W 6, a parameter that can be linked to occupation by different chemical species in the next nearest neighbouring sites. This parameter allows to clearly distinguish bacterial and abiotic calcite. This latter achievement was obtained after having reduced the parameters space into an unbiased Euclidean one, through an isometric log-ratio transformation. We conclude that this approach enables the coupled use of XRPD and EPR for identifying the traces of bacterial activity in fossil carbonate deposits.

Effect of Geometric Parameters on Formability and Strain Path During Tube Hydrforming Process

NASA Astrophysics Data System (ADS)

Omar, A.; Harisankar, K. R.; Tewari, Asim; Narasimhan, K.

2016-08-01

Forming limit diagram (FLD) is an important tool to measure the material's formability for metal forming processes. In order to successfully manufacture a component through tube hydroforming process it is very important to know the effect of material properties, process and geometrical parameters on the outcome of finished product. This can be obtained by running a finite element code which not only saves time and money but also gives a result with considerable accuracy. Therefore, in this paper the mutual effect of diameter as well as thickness has been studied. Firstly the finite element based prediction is carried out to assess the formability of seamless and welded tubes with varying thickness. Later on, effect of varying diameter and thickness on strain path is predicted using statistical based regression analysis. Finally, the mutual effect of varying material property alongwith varying thickness and diameter on constraint factor is studied.

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

NASA Astrophysics Data System (ADS)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

Bayesian Analysis of Non-Gaussian Long-Range Dependent Processes

NASA Astrophysics Data System (ADS)

Graves, T.; Franzke, C.; Gramacy, R. B.; Watkins, N. W.

2012-12-01

Recent studies have strongly suggested that surface temperatures exhibit long-range dependence (LRD). The presence of LRD would hamper the identification of deterministic trends and the quantification of their significance. It is well established that LRD processes exhibit stochastic trends over rather long periods of time. Thus, accurate methods for discriminating between physical processes that possess long memory and those that do not are an important adjunct to climate modeling. We have used Markov Chain Monte Carlo algorithms to perform a Bayesian analysis of Auto-Regressive Fractionally-Integrated Moving-Average (ARFIMA) processes, which are capable of modeling LRD. Our principal aim is to obtain inference about the long memory parameter, d,with secondary interest in the scale and location parameters. We have developed a reversible-jump method enabling us to integrate over different model forms for the short memory component. We initially assume Gaussianity, and have tested the method on both synthetic and physical time series such as the Central England Temperature. Many physical processes, for example the Faraday time series from Antarctica, are highly non-Gaussian. We have therefore extended this work by weakening the Gaussianity assumption. Specifically, we assume a symmetric α -stable distribution for the innovations. Such processes provide good, flexible, initial models for non-Gaussian processes with long memory. We will present a study of the dependence of the posterior variance σ d of the memory parameter d on the length of the time series considered. This will be compared with equivalent error diagnostics for other measures of d.

DISCRETE COMPOUND POISSON PROCESSES AND TABLES OF THE GEOMETRIC POISSON DISTRIBUTION.

DTIC Science & Technology

A concise summary of the salient properties of discrete Poisson processes , with emphasis on comparing the geometric and logarithmic Poisson processes . The...the geometric Poisson process are given for 176 sets of parameter values. New discrete compound Poisson processes are also introduced. These...processes have properties that are particularly relevant when the summation of several different Poisson processes is to be analyzed. This study provides the

Analysis of parameters for technological equipment of parallel kinematics based on rods of variable length for processing accuracy assurance

NASA Astrophysics Data System (ADS)

Koltsov, A. G.; Shamutdinov, A. H.; Blokhin, D. A.; Krivonos, E. V.

2018-01-01

A new classification of parallel kinematics mechanisms on symmetry coefficient, being proportional to mechanism stiffness and accuracy of the processing product using the technological equipment under study, is proposed. A new version of the Stewart platform with a high symmetry coefficient is presented for analysis. The workspace of the mechanism under study is described, this space being a complex solid figure. The workspace end points are reached by the center of the mobile platform which moves in parallel related to the base plate. Parameters affecting the processing accuracy, namely the static and dynamic stiffness, natural vibration frequencies are determined. The capability assessment of the mechanism operation under various loads, taking into account resonance phenomena at different points of the workspace, was conducted. The study proved that stiffness and therefore, processing accuracy with the use of the above mentioned mechanisms are comparable with the stiffness and accuracy of medium-sized series-produced machines.

Optimization of electrocoagulation process for the treatment of landfill leachate

NASA Astrophysics Data System (ADS)

Huda, N.; Raman, A. A.; Ramesh, S.

2017-06-01

The main problem of landfill leachate is its diverse composition comprising of persistent organic pollutants (POPs) which must be removed before being discharge into the environment. In this study, the treatment of leachate using electrocoagulation (EC) was investigated. Iron was used as both the anode and cathode. Response surface methodology was used for experimental design and to study the effects of operational parameters. Central Composite Design was used to study the effects of initial pH, inter-electrode distance, and electrolyte concentration on color, and COD removals. The process could remove up to 84 % color and 49.5 % COD. The experimental data was fitted onto second order polynomial equations. All three factors were found to be significantly affect the color removal. On the other hand, electrolyte concentration was the most significant parameter affecting the COD removal. Numerical optimization was conducted to obtain the optimum process performance. Further work will be conducted towards integrating EC with other wastewater treatment processes such as electro-Fenton.

The effect of reaction conditions on formation of wet precipitated calcium phosphates

NASA Astrophysics Data System (ADS)

Huang, Chen; Cao, Peng

2015-03-01

The precipitation process discussed in the present study involves the addition of alkaline solutions to an acidic calcium phosphate suspension. Several parameters (pH, pH buffer reagent, ageing and stirring) were investigated. The synthesized powders were calcined at 1000°C for 1 h in air, in order to study the thermal stability and crystalline phase compositions. X-ray diffraction (XRD) and ESEM analysis were used for sample characterization. It is found that all these processing parameters affect the crystalline phases evolved and resultant microstructures. Phase evolution occurred at an elevated pH level. The pH buffer reagent would affect both the phase composition and microstructure. Ageing was essential for the phase maturation. Stirring accelerated the reaction process by providing a homogeneous medium for precipitation.

Influence on surface characteristics of electron beam melting process (EBM) by varying the process parameters

NASA Astrophysics Data System (ADS)

Dolimont, Adrien; Michotte, Sebastien; Rivière-Lorphèvre, Edouard; Ducobu, François; Vivès, Solange; Godet, Stéphane; Henkes, Tom; Filippi, Enrico

2017-10-01

The use of additive manufacturing processes keeps growing in aerospace and biomedical industry. Among the numerous existing technologies, the Electron Beam Melting process has advantages (good dimensional accuracy, fully dense parts) and disadvantages (powder handling, support structure, high surface roughness). Analyzes of the surface characteristics are interesting to get a better understanding of the EBM operations. But that kind of analyzes is not often found in the literature. The main goal of this study is to determine if it is possible to improve the surface roughness by modifying some parameters of the process (scan speed function, number of contours, order of contours, etc.) on samples with different thicknesses. The experimental work on the surface roughness leads to a statistical analysis of 586 measures of EBM simple geometry parts.

Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data.

PubMed

Rakitzis, Athanasios C; Castagliola, Philippe; Maravelakis, Petros E

2018-02-01

In this work, we study upper-sided cumulative sum control charts that are suitable for monitoring geometrically inflated Poisson processes. We assume that a process is properly described by a two-parameter extension of the zero-inflated Poisson distribution, which can be used for modeling count data with an excessive number of zero and non-zero values. Two different upper-sided cumulative sum-type schemes are considered, both suitable for the detection of increasing shifts in the average of the process. Aspects of their statistical design are discussed and their performance is compared under various out-of-control situations. Changes in both parameters of the process are considered. Finally, the monitoring of the monthly cases of poliomyelitis in the USA is given as an illustrative example.

Influence of the heat transfer on the thermoelastic response of metals on heating by the laser pulse

NASA Astrophysics Data System (ADS)

Sudenkov, Y. V.; Zimin, B. A.; Sventitskaya, V. E.

2018-05-01

The paper presents an analysis of the effect of the heat transfer process in metals on the parameters of thermal stresses under pulsed laser action. The dynamic problem of thermoelasticity is considered as a two-stage process. The first stage is determined by the time of action of the radiation pulse. The second stage is caused by the dynamics of the heat transfer process after the end of the laser pulse. For showing the continuity of thermoelastic and thermoelectric processes, the analysis of the electronic mechanism for the propagation of heat in metals and the results of experimental studies of these processes are presented. The results of the experiments demonstrate the high sensitivity of the parameters of thermoelastic and thermoelectric pulses to the microstructure of metals.

Analysis of latency performance of bluetooth low energy (BLE) networks.

PubMed

Cho, Keuchul; Park, Woojin; Hong, Moonki; Park, Gisu; Cho, Wooseong; Seo, Jihoon; Han, Kijun

2014-12-23

Bluetooth Low Energy (BLE) is a short-range wireless communication technology aiming at low-cost and low-power communication. The performance evaluation of classical Bluetooth device discovery have been intensively studied using analytical modeling and simulative methods, but these techniques are not applicable to BLE, since BLE has a fundamental change in the design of the discovery mechanism, including the usage of three advertising channels. Recently, there several works have analyzed the topic of BLE device discovery, but these studies are still far from thorough. It is thus necessary to develop a new, accurate model for the BLE discovery process. In particular, the wide range settings of the parameters introduce lots of potential for BLE devices to customize their discovery performance. This motivates our study of modeling the BLE discovery process and performing intensive simulation. This paper is focused on building an analytical model to investigate the discovery probability, as well as the expected discovery latency, which are then validated via extensive experiments. Our analysis considers both continuous and discontinuous scanning modes. We analyze the sensitivity of these performance metrics to parameter settings to quantitatively examine to what extent parameters influence the performance metric of the discovery processes.

Analysis of Latency Performance of Bluetooth Low Energy (BLE) Networks

PubMed Central

Cho, Keuchul; Park, Woojin; Hong, Moonki; Park, Gisu; Cho, Wooseong; Seo, Jihoon; Han, Kijun

2015-01-01

Bluetooth Low Energy (BLE) is a short-range wireless communication technology aiming at low-cost and low-power communication. The performance evaluation of classical Bluetooth device discovery have been intensively studied using analytical modeling and simulative methods, but these techniques are not applicable to BLE, since BLE has a fundamental change in the design of the discovery mechanism, including the usage of three advertising channels. Recently, there several works have analyzed the topic of BLE device discovery, but these studies are still far from thorough. It is thus necessary to develop a new, accurate model for the BLE discovery process. In particular, the wide range settings of the parameters introduce lots of potential for BLE devices to customize their discovery performance. This motivates our study of modeling the BLE discovery process and performing intensive simulation. This paper is focused on building an analytical model to investigate the discovery probability, as well as the expected discovery latency, which are then validated via extensive experiments. Our analysis considers both continuous and discontinuous scanning modes. We analyze the sensitivity of these performance metrics to parameter settings to quantitatively examine to what extent parameters influence the performance metric of the discovery processes. PMID:25545266

Maximising municipal solid waste--legume trimming residue mixture degradation in composting by control parameters optimization.

PubMed

Cabeza, I O; López, R; Ruiz-Montoya, M; Díaz, M J

2013-10-15

Composting is one of the most successful biological processes for the treatment of the residues enriched in putrescible materials. The optimization of parameters which have an influence on the stability of the products is necessary in order to maximize recycling and recovery of waste components. The influence of the composting process parameters (aeration, moisture, C/N ratio, and time) on the stability parameters (organic matter, N-losses, chemical oxygen demand, nitrate, biodegradability coefficient) of the compost was studied. The composting experiment was carried out using Municipal Solid Waste (MSW) and Legume Trimming Residues (LTR) in 200 L isolated acrylic barrels following a Box-Behnken central composite experimental design. Second-order polynomial models were found for each of the studied compost stability parameter, which accurately described the relationship between the parameters. The differences among the experimental values and those estimated by using the equations never exceeded 10% of the former. Results of the modelling showed that excluding the time, the C/N ratio is the strongest variable influencing almost all the stability parameters studied in this case, with the exception of N-losses which is strongly dependent on moisture. Moreover, an optimized ratio MSW/LTR of 1/1 (w/w), moisture content in the range of 40-55% and moderate to low aeration rate (0.05-0.175 Lair kg(-)(1) min(-1)) is recommended to maximise degradation and to obtain a stable product during co-composting of MSW and LTR. Copyright © 2013 Elsevier Ltd. All rights reserved.

The CRDS method application for study of the gas-phase processes in the hot CVD diamond thin film.

NASA Astrophysics Data System (ADS)

Buzaianumakarov, Vladimir; Hidalgo, Arturo; Morell, Gerardo; Weiner, Brad; Buzaianu, Madalina

2006-03-01

For detailed analysis of problem related to the hot CVD carbon-containing nano-material growing, we have to detect different intermediate species forming during the growing process as well as investigate dependences of concentrations of these species on different experimental parameters (concentrations of the CJH4, H2S stable chemical compounds and distance from the filament system to the substrate surface). In the present study, the HS and CS radicals were detected using the Cavity Ring Down Spectroscopic (CRDS) method in the hot CVD diamond thin film for the CH4(0.4 %) + H2 mixture doped by H2S (400 ppm). The absolute absorption density spectra of the HS and CS radicals were obtained as a function of different experimental parameters. This study proofs that the HS and CS radicals are an intermediate, which forms during the hot filament CVD process. The kinetics approach was developed for detailed analysis of the experimental data obtained. The kinetics scheme includes homogenous and heterogenous processes as well as processes of the chemical species transport in the CVD chamber.

Experimental Study of Heat Transfer Performance of Polysilicon Slurry Drying Process

NASA Astrophysics Data System (ADS)

Wang, Xiaojing; Ma, Dongyun; Liu, Yaqian; Wang, Zhimin; Yan, Yangyang; Li, Yuankui

2016-12-01

In recent years, the growth of the solar energy photovoltaic industry has greatly promoted the development of polysilicon. However, there has been little research into the slurry by-products of polysilicon production. In this paper the thermal performance of polysilicon slurry was studied in an industrial drying process with a twin-screw horizontal intermittent dryer. By dividing the drying process into several subunits, the parameters of each unit could be regarded as constant in that period. The time-dependent changes in parameters including temperature, specific heat and evaporation enthalpy were plotted. An equation for the change in the heat transfer coefficient over time was calculated based on heat transfer equations. The concept of a distribution coefficient was introduced to reflect the influence of stirring on the heat transfer area. The distribution coefficient ranged from 1.2 to 1.7 and was obtained with the fluid simulation software FLUENT, which simplified the calculation of heat transfer area during the drying process. These experimental data can be used to guide the study of polysilicon slurry drying and optimize the design of dryers for industrial processes.

Analytical and regression models of glass rod drawing process

NASA Astrophysics Data System (ADS)

Alekseeva, L. B.

2018-03-01

The process of drawing glass rods (light guides) is being studied. The parameters of the process affecting the quality of the light guide have been determined. To solve the problem, mathematical models based on general equations of continuum mechanics are used. The conditions for the stable flow of the drawing process have been found, which are determined by the stability of the motion of the glass mass in the formation zone to small uncontrolled perturbations. The sensitivity of the formation zone to perturbations of the drawing speed and viscosity is estimated. Experimental models of the drawing process, based on the regression analysis methods, have been obtained. These models make it possible to customize a specific production process to obtain light guides of the required quality. They allow one to find the optimum combination of process parameters in the chosen area and to determine the required accuracy of maintaining them at a specified level.

Sorptive removal of nickel onto weathered basaltic andesite products: kinetics and isotherms.

PubMed

Shah, Bhavna A; Shah, Ajay V; Singh, Rajesh R; Patel, Nayan B

2009-07-15

The suitability of weathered basaltic andesite products (WBAP) as a potential sorbent was assessed for the removal of Ni (II) from electroplating industrial wastewater. A model study based on the batch mode of operation was carried out for Ni (II) removal from aqueous solution. The effect of various parameters such as hydronium ion concentration, shaking time, sorbent dose, initial Ni (II) concentration, and temperature on the sorption process was studied. At optimised conditions of the various parameters, the industrial wastewater loaded with Ni (II) was sorbed onto WBAP. Thermodynamic parameters for the sorption process were evaluated. Freundlich, Langmuir, Temkin, and Dubinin-Kaganer-Radushkevich isotherms were applied to the sorption pattern on the WBAP. The sorption dynamics of the process was evaluated by applying Lagergren, Bangham, and Weber & Morris equations. The sorption process follows Pseudo-second-order rate of surface diffusion which is identified as the predominating mechanism. The sorption process was found to be reversible by the recovery of sorbed Ni (II) upon extraction with 0.5 MHNO3. The sorbent before and after sorption, was characterized by Fourier transform infrared (FTIR), Powder X-Ray diffraction PXRD), and Thermogravimetric analysis (TGA) methods. The change in surface morphology and crystallanity of the mineral after sorption was analyzed by Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM). Based on the previous model study, an electroplating industrial effluent was successfully treated with WBAP to minimize the pollution load caused by Ni (II).

Effects of image processing on the detective quantum efficiency

NASA Astrophysics Data System (ADS)

Park, Hye-Suk; Kim, Hee-Joung; Cho, Hyo-Min; Lee, Chang-Lae; Lee, Seung-Wan; Choi, Yu-Na

2010-04-01

Digital radiography has gained popularity in many areas of clinical practice. This transition brings interest in advancing the methodologies for image quality characterization. However, as the methodologies for such characterizations have not been standardized, the results of these studies cannot be directly compared. The primary objective of this study was to standardize methodologies for image quality characterization. The secondary objective was to evaluate affected factors to Modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) according to image processing algorithm. Image performance parameters such as MTF, NPS, and DQE were evaluated using the international electro-technical commission (IEC 62220-1)-defined RQA5 radiographic techniques. Computed radiography (CR) images of hand posterior-anterior (PA) for measuring signal to noise ratio (SNR), slit image for measuring MTF, white image for measuring NPS were obtained and various Multi-Scale Image Contrast Amplification (MUSICA) parameters were applied to each of acquired images. In results, all of modified images were considerably influence on evaluating SNR, MTF, NPS, and DQE. Modified images by the post-processing had higher DQE than the MUSICA=0 image. This suggests that MUSICA values, as a post-processing, have an affect on the image when it is evaluating for image quality. In conclusion, the control parameters of image processing could be accounted for evaluating characterization of image quality in same way. The results of this study could be guided as a baseline to evaluate imaging systems and their imaging characteristics by measuring MTF, NPS, and DQE.

Technical Parameters Modeling of a Gas Probe Foaming Using an Active Experimental Type Research

NASA Astrophysics Data System (ADS)

Tîtu, A. M.; Sandu, A. V.; Pop, A. B.; Ceocea, C.; Tîtu, S.

2018-06-01

The present paper deals with a current and complex topic, namely - a technical problem solving regarding the modeling and then optimization of some technical parameters related to the natural gas extraction process. The study subject is to optimize the gas probe sputtering using experimental research methods and data processing by regular probe intervention with different sputtering agents. This procedure makes that the hydrostatic pressure to be reduced by the foam formation from the water deposit and the scrubbing agent which can be removed from the surface by the produced gas flow. The probe production data was analyzed and the so-called candidate for the research itself emerged. This is an extremely complex study and it was carried out on the field works, finding that due to the severe gas field depletion the wells flow decreases and the start of their loading with deposit water, was registered. It was required the regular wells foaming, to optimize the daily production flow and the disposal of the wellbore accumulated water. In order to analyze the process of natural gas production, the factorial experiment and other methods were used. The reason of this choice is that the method can offer very good research results with a small number of experimental data. Finally, through this study the extraction process problems were identified by analyzing and optimizing the technical parameters, which led to a quality improvement of the extraction process.

Modeling and optimization of joint quality for laser transmission joint of thermoplastic using an artificial neural network and a genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiao; Zhang, Cheng; Li, Pin; Wang, Kai; Hu, Yang; Zhang, Peng; Liu, Huixia

2012-11-01

A central composite rotatable experimental design(CCRD) is conducted to design experiments for laser transmission joining of thermoplastic-Polycarbonate (PC). The artificial neural network was used to establish the relationships between laser transmission joining process parameters (the laser power, velocity, clamp pressure, scanning number) and joint strength and joint seam width. The developed mathematical models are tested by analysis of variance (ANOVA) method to check their adequacy and the effects of process parameters on the responses and the interaction effects of key process parameters on the quality are analyzed and discussed. Finally, the desirability function coupled with genetic algorithm is used to carry out the optimization of the joint strength and joint width. The results show that the predicted results of the optimization are in good agreement with the experimental results, so this study provides an effective method to enhance the joint quality.

Characteristics of Friction Stir Processed UHMW Polyethylene Based Composite

NASA Astrophysics Data System (ADS)

Hussain, G.; Khan, I.

2018-01-01

Ultra-high molecular weight polyethylene (UHMWPE) based composites are widely used in biomedical and food industries because of their biocompatibility and enhanced properties. The aim of this study was to fabricate UHMWPE / nHA composite through heat assisted Friction Stir Processing. The rotational speed (ω), feed rate (f), volume fraction of nHA (v) and shoulder temperature (T) were selected as the process parameters. Macroscopic and microscopic analysis revealed that these parameters have significant effects on the distribution of reinforcing material, defects formation and material mixing. Defects were observed especially at low levels of (ω, T) and high levels of (f, v). Low level of v with medium levels of other parameters resulted in better mixing and minimum defects. A 10% increase in strength with only 1% reduction in Percent Elongation was observed at the above set of conditions. Moreover, the resulted hardness of the composite was higher than that of the parent material.

Consumer perception of dry-cured sheep meat products: Influence of process parameters under different evoked contexts.

PubMed

de Andrade, Juliana Cunha; Nalério, Elen Silveira; Giongo, Citieli; de Barcellos, Marcia Dutra; Ares, Gastón; Deliza, Rosires

2017-08-01

The development of high-quality air-dried cured sheep meat products adapted to meet consumer demands represent an interesting option to add value to the meat of adult animals. The present study aimed to evaluate the influence of process parameters on consumer choice of two products from sheep meat under different evoked contexts, considering product concepts. A total of 375 Brazilian participants completed a choice-based conjoint task with three 2-level variables for each product: maturation time, smoking, and sodium reduction for dry-cured sheep ham, and natural antioxidant, smoking, and sodium reduction for sheep meat coppa. A between-subjects experimental design was used to evaluate the influence of consumption context on consumer choices. All the process parameters significantly influenced consumer choice. However, their relative importance was affected by evoked context. Copyright © 2017. Published by Elsevier Ltd.

Modelling of influential parameters on a continuous evaporation process by Doehlert shells

PubMed Central

Porte, Catherine; Havet, Jean-Louis; Daguet, David

2003-01-01

The modelling of the parameters that influence the continuous evaporation of an alcoholic extract was considered using Doehlert matrices. The work was performed with a wiped falling film evaporator that allowed us to study the influence of the pressure, temperature, feed flow and dry matter of the feed solution on the dry matter contents of the resulting concentrate, and the productivity of the process. The Doehlert shells were used to model the influential parameters. The pattern obtained from the experimental results was checked allowing for some dysfunction in the unit. The evaporator was modified and a new model applied; the experimental results were then in agreement with the equations. The model was finally determined and successfully checked in order to obtain an 8% dry matter concentrate with the best productivity; the results fit in with the industrial constraints of subsequent processes. PMID:18924887

Numerical simulation of electron beam welding with beam oscillations

NASA Astrophysics Data System (ADS)

Trushnikov, D. N.; Permyakov, G. L.

2017-02-01

This research examines the process of electron-beam welding in a keyhole mode with the use of beam oscillations. We study the impact of various beam oscillations and their parameters on the shape of the keyhole, the flow of heat and mass transfer processes and weld parameters to develop methodological recommendations. A numerical three-dimensional mathematical model of electron beam welding is presented. The model was developed on the basis of a heat conduction equation and a Navier-Stokes equation taking into account phase transitions at the interface of a solid and liquid phase and thermocapillary convection (Marangoni effect). The shape of the keyhole is determined based on experimental data on the parameters of the secondary signal by using the method of a synchronous accumulation. Calculations of thermal and hydrodynamic processes were carried out based on a computer cluster, using a simulation package COMSOL Multiphysics.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

Parametric study on single shot peening by dimensional analysis method incorporated with finite element method

NASA Astrophysics Data System (ADS)

Wu, Xian-Qian; Wang, Xi; Wei, Yan-Peng; Song, Hong-Wei; Huang, Chen-Guang

2012-06-01

Shot peening is a widely used surface treatment method by generating compressive residual stress near the surface of metallic materials to increase fatigue life and resistance to corrosion fatigue, cracking, etc. Compressive residual stress and dent profile are important factors to evaluate the effectiveness of shot peening process. In this paper, the influence of dimensionless parameters on maximum compressive residual stress and maximum depth of the dent were investigated. Firstly, dimensionless relations of processing parameters that affect the maximum compressive residual stress and the maximum depth of the dent were deduced by dimensional analysis method. Secondly, the influence of each dimensionless parameter on dimensionless variables was investigated by the finite element method. Furthermore, related empirical formulas were given for each dimensionless parameter based on the simulation results. Finally, comparison was made and good agreement was found between the simulation results and the empirical formula, which shows that a useful approach is provided in this paper for analyzing the influence of each individual parameter.

Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

NASA Astrophysics Data System (ADS)

Miao, Changyun; Shi, Boya; Li, Hongqiang

2008-12-01

A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

Experimental investigation and optimization of welding process parameters for various steel grades using NN tool and Taguchi method

NASA Astrophysics Data System (ADS)

Soni, Sourabh Kumar; Thomas, Benedict

2018-04-01

The term "weldability" has been used to describe a wide variety of characteristics when a material is subjected to welding. In our analysis we perform experimental investigation to estimate the tensile strength of welded joint strength and then optimization of welding process parameters by using taguchi method and Artificial Neural Network (ANN) tool in MINITAB and MATLAB software respectively. The study reveals the influence on weldability of steel by varying composition of steel by mechanical characterization. At first we prepare the samples of different grades of steel (EN8, EN 19, EN 24). The samples were welded together by metal inert gas welding process and then tensile testing on Universal testing machine (UTM) was conducted for the same to evaluate the tensile strength of the welded steel specimens. Further comparative study was performed to find the effects of welding parameter on quality of weld strength by employing Taguchi method and Neural Network tool. Finally we concluded that taguchi method and Neural Network Tool is much efficient technique for optimization.

The impact of temporal sampling resolution on parameter inference for biological transport models.

PubMed

Harrison, Jonathan U; Baker, Ruth E

2018-06-25

Imaging data has become an essential tool to explore key biological questions at various scales, for example the motile behaviour of bacteria or the transport of mRNA, and it has the potential to transform our understanding of important transport mechanisms. Often these imaging studies require us to compare biological species or mutants, and to do this we need to quantitatively characterise their behaviour. Mathematical models offer a quantitative description of a system that enables us to perform this comparison, but to relate mechanistic mathematical models to imaging data, we need to estimate their parameters. In this work we study how collecting data at different temporal resolutions impacts our ability to infer parameters of biological transport models; performing exact inference for simple velocity jump process models in a Bayesian framework. The question of how best to choose the frequency with which data is collected is prominent in a host of studies because the majority of imaging technologies place constraints on the frequency with which images can be taken, and the discrete nature of observations can introduce errors into parameter estimates. In this work, we mitigate such errors by formulating the velocity jump process model within a hidden states framework. This allows us to obtain estimates of the reorientation rate and noise amplitude for noisy observations of a simple velocity jump process. We demonstrate the sensitivity of these estimates to temporal variations in the sampling resolution and extent of measurement noise. We use our methodology to provide experimental guidelines for researchers aiming to characterise motile behaviour that can be described by a velocity jump process. In particular, we consider how experimental constraints resulting in a trade-off between temporal sampling resolution and observation noise may affect parameter estimates. Finally, we demonstrate the robustness of our methodology to model misspecification, and then apply our inference framework to a dataset that was generated with the aim of understanding the localization of RNA-protein complexes.

Coherence Measurements for Excited to Excited State Transitions in Barium

NASA Technical Reports Server (NTRS)

Trajmar, S.; Kanik, I.; Karaganov, V.; Zetner, P. W.; Csanak, G.

2000-01-01

Experimental studies concerning elastic and inelastic electron scattering by coherently ensembles of Ba (...6s6p (sub 1)P(sub 1)) atoms with various degrees of alignment will be described. An in-plane, linearly-polarized laser beam was utilized to prepare these target ensembles and the electron scattering signal as a function of polarization angle was measured for several laser geometries at fixed impact energies and scattering angles. From these measurements, we derived cross sections and electron-impact coherence parameters associated with the electron scattering process which is time reverse of the actual experimentally studied process. This interpretation of the experiment is based on the theory of Macek and Herte. The experimental results were also interpreted in terms of cross sections and collision parameters associated with the actual experimental processes. Results obtained so far will be presented and plans for further studies will be discussed.

Modeling of feed-forward control using the partial least squares regression method in the tablet compression process.

PubMed

Hattori, Yusuke; Otsuka, Makoto

2017-05-30

In the pharmaceutical industry, the implementation of continuous manufacturing has been widely promoted in lieu of the traditional batch manufacturing approach. More specially, in recent years, the innovative concept of feed-forward control has been introduced in relation to process analytical technology. In the present study, we successfully developed a feed-forward control model for the tablet compression process by integrating data obtained from near-infrared (NIR) spectra and the physical properties of granules. In the pharmaceutical industry, batch manufacturing routinely allows for the preparation of granules with the desired properties through the manual control of process parameters. On the other hand, continuous manufacturing demands the automatic determination of these process parameters. Here, we proposed the development of a control model using the partial least squares regression (PLSR) method. The most significant feature of this method is the use of dataset integrating both the NIR spectra and the physical properties of the granules. Using our model, we determined that the properties of products, such as tablet weight and thickness, need to be included as independent variables in the PLSR analysis in order to predict unknown process parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigation of Parametric Influence on the Properties of Al6061-SiCp Composite

NASA Astrophysics Data System (ADS)

Adebisi, A. A.; Maleque, M. A.; Bello, K. A.

2017-03-01

The influence of process parameter in stir casting play a major role on the development of aluminium reinforced silicon carbide particle (Al-SiCp) composite. This study aims to investigate the influence of process parameters on wear and density properties of Al-SiCp composite using stir casting technique. Experimental data are generated based on a four-factors-five-level central composite design of response surface methodology. Analysis of variance is utilized to confirm the adequacy and validity of developed models considering the significant model terms. Optimization of the process parameters adequately predicts the Al-SiCp composite properties with stirring speed as the most influencing factor. The aim of optimization process is to minimize wear and maximum density. The multiple objective optimization (MOO) achieved an optimal value of 14 wt% reinforcement fraction (RF), 460 rpm stirring speed (SS), 820 °C processing temperature (PTemp) and 150 secs processing time (PT). Considering the optimum parametric combination, wear mass loss achieved a minimum of 1 x 10-3 g and maximum density value of 2.780g/mm3 with a confidence and desirability level of 95.5%.

Towards Limits on Neutrino Mixing Parameters from Nucleosynthesis in the Big Bang and Supernovae

NASA Astrophysics Data System (ADS)

Cardall, Christian Young

1997-11-01

Astrophysical environments can often provide stricter limits on neutrino mass and mixing parameters than terrestrial experiments. However, before firm limits can be found, there must be confidence in the understanding of the astrophysical environment being used to make these limits. In this dissertation, progress towards limits on neutrino mixing parameters from big bang nucleosynthesis and supernova r-process nucleosynthesis is sought. By way of assessment of current knowledge of neutrino oscillation parameters, we examine the potential for a 'natural' three-neutrino mixing scheme (one without sterile neutrinos) to satisfy available data and astrophysical arguments. A small parameter space currently exists for a natural three-neutrino oscillation solution meeting known constraints. If such a solution is ruled out, and current hints about neutrino oscillations are confirmed, mixing between active and sterile neutrinos will probably be required. Because mixing between active and sterile neutrinos with parameters appropriate for the atmospheric or solar neutrino problems increases the primordial 4He abundance, big bang nucleosynthesis considerations can place limits on such mixing. In the present work the overall consistency of standard big bang nucleosynthesis is discussed in light of recent discordant determinations of the primordial deuterium abundance. Cosmological considerations favor a larger baryon density, which supports the lower reported value of D/H. Studies of limits on active-sterile neutrino mixing derived from big bang nucleosynthesis considerations are here extended to consider the dependance of these constraints on the primordial deuterium abundance. If the neutrino-heated ejecta in the post-core-bounce supernova environment is the site of r-process nucleosynthesis, limits can be placed on mixing between νe, and νsbμ, or νsbτ. Refined limits will require a better understanding of this r-process environment, since current supernova models do not show a completely successful r-process. In this work it is shown that general relativistic effects associated with a more compact supernova core can provide more suitable conditions for the r-process. As a step towards analyzing the effects of neutrino mixing in such a relativistic environment, neutrino oscillations in curved spacetime are studied.

Vapor hydrogen peroxide as alternative to dry heat microbial reduction

NASA Astrophysics Data System (ADS)

Chung, S.; Kern, R.; Koukol, R.; Barengoltz, J.; Cash, H.

2008-09-01

The Jet Propulsion Laboratory (JPL), in conjunction with the NASA Planetary Protection Officer, has selected vapor phase hydrogen peroxide (VHP) sterilization process for continued development as a NASA approved sterilization technique for spacecraft subsystems and systems. The goal was to include this technique, with an appropriate specification, in NASA Procedural Requirements 8020.12 as a low-temperature complementary technique to the dry heat sterilization process. The VHP process is widely used by the medical industry to sterilize surgical instruments and biomedical devices, but high doses of VHP may degrade the performance of flight hardware, or compromise material compatibility. The goal for this study was to determine the minimum VHP process conditions for planetary protection acceptable microbial reduction levels. Experiments were conducted by the STERIS Corporation, under contract to JPL, to evaluate the effectiveness of vapor hydrogen peroxide for the inactivation of the standard spore challenge, Geobacillus stearothermophilus. VHP process parameters were determined that provide significant reductions in spore viability while allowing survival of sufficient spores for statistically significant enumeration. In addition to the obvious process parameters of interest: hydrogen peroxide concentration, number of injection cycles, and exposure duration, the investigation also considered the possible effect on lethality of environmental parameters: temperature, absolute humidity, and material substrate. This study delineated a range of test sterilizer process conditions: VHP concentration, process duration, a process temperature range for which the worst case D-value may be imposed, a process humidity range for which the worst case D-value may be imposed, and the dependence on selected spacecraft material substrates. The derivation of D-values from the lethality data permitted conservative planetary protection recommendations.

A Hierarchical Bayesian Model for Calibrating Estimates of Species Divergence Times

PubMed Central

Heath, Tracy A.

2012-01-01

In Bayesian divergence time estimation methods, incorporating calibrating information from the fossil record is commonly done by assigning prior densities to ancestral nodes in the tree. Calibration prior densities are typically parametric distributions offset by minimum age estimates provided by the fossil record. Specification of the parameters of calibration densities requires the user to quantify his or her prior knowledge of the age of the ancestral node relative to the age of its calibrating fossil. The values of these parameters can, potentially, result in biased estimates of node ages if they lead to overly informative prior distributions. Accordingly, determining parameter values that lead to adequate prior densities is not straightforward. In this study, I present a hierarchical Bayesian model for calibrating divergence time analyses with multiple fossil age constraints. This approach applies a Dirichlet process prior as a hyperprior on the parameters of calibration prior densities. Specifically, this model assumes that the rate parameters of exponential prior distributions on calibrated nodes are distributed according to a Dirichlet process, whereby the rate parameters are clustered into distinct parameter categories. Both simulated and biological data are analyzed to evaluate the performance of the Dirichlet process hyperprior. Compared with fixed exponential prior densities, the hierarchical Bayesian approach results in more accurate and precise estimates of internal node ages. When this hyperprior is applied using Markov chain Monte Carlo methods, the ages of calibrated nodes are sampled from mixtures of exponential distributions and uncertainty in the values of calibration density parameters is taken into account. PMID:22334343

Using frequency analysis to improve the precision of human body posture algorithms based on Kalman filters.

PubMed

Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, G

2016-05-01

With the advent of miniaturized inertial sensors many systems have been developed within the last decade to study and analyze human motion and posture, specially in the medical field. Data measured by the sensors are usually processed by algorithms based on Kalman Filters in order to estimate the orientation of the body parts under study. These filters traditionally include fixed parameters, such as the process and observation noise variances, whose value has large influence in the overall performance. It has been demonstrated that the optimal value of these parameters differs considerably for different motion intensities. Therefore, in this work, we show that, by applying frequency analysis to determine motion intensity, and varying the formerly fixed parameters accordingly, the overall precision of orientation estimation algorithms can be improved, therefore providing physicians with reliable objective data they can use in their daily practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Constraints of beyond Standard Model parameters from the study of neutrinoless double beta decay

NASA Astrophysics Data System (ADS)

Stoica, Sabin

2017-12-01

Neutrinoless double beta (0νββ) decay is a beyond Standard Model (BSM) process whose discovery would clarify if the lepton number is conserved, decide on the neutrinos character (are they Dirac or Majorana particles?) and give a hint on the scale of their absolute masses. Also, from the study of 0νββ one can constrain other BSM parameters related to different scenarios by which this process can occur. In this paper I make first a short review on the actual challenges to calculate precisely the phase space factors and nuclear matrix elements entering the 0νββ decay lifetimes, and I report results of our group for these quantities. Then, taking advance of the most recent experimental limits for 0νββ lifetimes, I present new constraints of the neutrino mass parameters associated with different mechanisms of occurrence of the 0νββ decay mode.

Cogeneration Technology Alternatives Study (CTAS). Volume 6: Computer data. Part 2: Residual-fired nocogeneration process boiler

NASA Technical Reports Server (NTRS)

Knightly, W. F.

1980-01-01

Computer generated data on the performance of the cogeneration energy conversion system are presented. Performance parameters included fuel consumption and savings, capital costs, economics, and emissions of residual fired process boilers.

Pulsed electric fields for pasteurization: defining processing conditions

USDA-ARS?s Scientific Manuscript database

Application of pulsed electric fields (PEF) technology in food pasteurization has been extensively studied. Optimal PEF treatment conditions for maximum microbial inactivation depend on multiple factors including PEF processing conditions, production parameters and product properties. In order for...

Etching Behavior of Aluminum Alloy Extrusions

NASA Astrophysics Data System (ADS)

Zhu, Hanliang

2014-11-01

The etching treatment is an important process step in influencing the surface quality of anodized aluminum alloy extrusions. The aim of etching is to produce a homogeneously matte surface. However, in the etching process, further surface imperfections can be generated on the extrusion surface due to uneven materials loss from different microstructural components. These surface imperfections formed prior to anodizing can significantly influence the surface quality of the final anodized extrusion products. In this article, various factors that influence the materials loss during alkaline etching of aluminum alloy extrusions are investigated. The influencing variables considered include etching process parameters, Fe-rich particles, Mg-Si precipitates, and extrusion profiles. This study provides a basis for improving the surface quality in industrial extrusion products by optimizing various process parameters.

Evaluation of ultrasound based sterilization approaches in terms of shelf life and quality parameters of fruit and vegetable juices.

PubMed

Khandpur, Paramjeet; Gogate, Parag R

2016-03-01

The present work evaluates the performance of ultrasound based sterilization approaches for processing of different fruit and vegetable juices in terms of microbial growth and changes in the quality parameters during the storage. Comparison with the conventional thermal processing has also been presented. A novel approach based on combination of ultrasound with ultraviolet irradiation and crude extract of essential oil from orange peels has been used for the first time. Identification of the microbial growth (total bacteria and yeast content) in the juices during the subsequent storage and assessing the safety for human consumption along with the changes in the quality parameters (Brix, titratable acidity, pH, ORP, salt, conductivity, TSS and TDS) has been investigated in details. The optimized ultrasound parameters for juice sterilization were established as ultrasound power of 100 W and treatment time of 15 min for the constant frequency operation (20 kHz). It has been established that more than 5 log reduction was achieved using the novel combined approaches based on ultrasound. The treated juices using different approaches based on ultrasound also showed lower microbial growth and improved quality characteristics as compared to the thermally processed juice. Scale up studies were also performed using spinach juice as the test sample with processing at 5 L volume for the first time. The ultrasound treated juice satisfied the microbiological and physiochemical safety limits in refrigerated storage conditions for 20 days for the large scale processing. Overall the present work conclusively established the usefulness of combined treatment approaches based on ultrasound for maintaining the microbiological safety of beverages with enhanced shelf life and excellent quality parameters as compared to the untreated and thermally processed juices. Copyright © 2015 Elsevier B.V. All rights reserved.

Use of in-die powder densification parameters in the implementation of process analytical technologies for tablet production on industrial scale.

PubMed

Cespi, Marco; Perinelli, Diego R; Casettari, Luca; Bonacucina, Giulia; Caporicci, Giuseppe; Rendina, Filippo; Palmieri, Giovanni F

2014-12-30

The use of process analytical technologies (PAT) to ensure final product quality is by now a well established practice in pharmaceutical industry. To date, most of the efforts in this field have focused on development of analytical methods using spectroscopic techniques (i.e., NIR, Raman, etc.). This work evaluated the possibility of using the parameters derived from the processing of in-line raw compaction data (the forces and displacement of the punches) as a PAT tool for controlling the tableting process. To reach this goal, two commercially available formulations were used, changing the quantitative composition and compressing them on a fully instrumented rotary pressing machine. The Heckel yield pressure and the compaction energies, together with the tablets hardness and compaction pressure, were selected and evaluated as discriminating parameters in all the prepared formulations. The apparent yield pressure, as shown in the obtained results, has the necessary sensitivity to be effectively included in a PAT strategy to monitor the tableting process. Additional investigations were performed to understand the criticalities and the mechanisms beyond this performing parameter and the associated implications. Specifically, it was discovered that the efficiency of the apparent yield pressure depends on the nominal drug title, the drug densification mechanism and the error in pycnometric density. In this study, the potential of using some parameters derived from the compaction raw data has been demonstrated to be an attractive alternative and complementary method to the well established spectroscopic techniques to monitor and control the tableting process. The compaction data monitoring method is also easy to set up and very cost effective. Copyright © 2014 Elsevier B.V. All rights reserved.

Using implicit association tests in age-heterogeneous samples: The importance of cognitive abilities and quad model processes.

PubMed

Wrzus, Cornelia; Egloff, Boris; Riediger, Michaela

2017-08-01

Implicit association tests (IATs) are increasingly used to indirectly assess people's traits, attitudes, or other characteristics. In addition to measuring traits or attitudes, IAT scores also reflect differences in cognitive abilities because scores are based on reaction times (RTs) and errors. As cognitive abilities change with age, questions arise concerning the usage and interpretation of IATs for people of different age. To address these questions, the current study examined how cognitive abilities and cognitive processes (i.e., quad model parameters) contribute to IAT results in a large age-heterogeneous sample. Participants (N = 549; 51% female) in an age-stratified sample (range = 12-88 years) completed different IATs and 2 tasks to assess cognitive processing speed and verbal ability. From the IAT data, D2-scores were computed based on RTs, and quad process parameters (activation of associations, overcoming bias, detection, guessing) were estimated from individual error rates. Substantial IAT scores and quad processes except guessing varied with age. Quad processes AC and D predicted D2-scores of the content-specific IAT. Importantly, the effects of cognitive abilities and quad processes on IAT scores were not significantly moderated by participants' age. These findings suggest that IATs seem suitable for age-heterogeneous studies from adolescence to old age when IATs are constructed and analyzed appropriately, for example with D-scores and process parameters. We offer further insight into how D-scoring controls for method effects in IATs and what IAT scores capture in addition to implicit representations of characteristics. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Physico-chemical, colorimetric, rheological parameters and chemometric discrimination of the origin of Mugil cephalus' roes during the manufacturing process of Bottarga.

PubMed

Caredda, Marco; Addis, Margherita; Pes, Massimo; Fois, Nicola; Sanna, Gabriele; Piredda, Giovanni; Sanna, Gavino

2018-06-01

The aim of this work was to measure the physico-chemical and the colorimetric parameters of ovaries from Mugil cephalus caught in the Tortolì lagoon (South-East coast of Sardinia) along the steps of the manufacturing process of Bottarga, together with the rheological parameters of the final product. A lowering of all CIELab coordinates (lightness, redness and yellowness) was observed during the manufacture process. All CIELab parameters were used to build a Linear Discriminant Analysis (LDA) predictive model able to determine in real time if the roes had been subdued to a freezing process, with a success in prediction of 100%. This model could be used to identify the origin of the roes, since only the imported ones are frozen. The major changes of all the studied parameters (p < 0.05) were noted in the drying step rather than in the salting step. After processing, Bottarga was characterized by a pH value of 5.46 (CV = 2.8) and a moisture content of 25% (CV = 8), whereas the typical per cent amounts of proteins, fat and NaCl, calculated as a percentage on the dried weight, were 56 (CV = 2), 34 (CV = 3) and 3.6 (CV = 17), respectively. The physical chemical changes of the roes during the manufacturing process were consistent for moisture, which decreased by 28%, whereas the protein and the fat contents on the dried weight got respectively lower of 3% and 2%. NaCl content increased by 3.1%. Principal Component Analyses (PCA) were also performed on all data to establish trends and relationships among all parameters. Hardness and consistency of Bottarga were negatively correlated with the moisture content (r = -0.87 and r = -0.88, respectively), while its adhesiveness was negatively correlated with the fat content (r = -0.68). Copyright © 2018. Published by Elsevier Ltd.

Adsorptive removal of aniline by granular activated carbon from aqueous solutions with catechol and resorcinol.

PubMed

Suresh, S; Srivastava, V C; Mishrab, I M

2012-01-01

In the present paper, the removal of aniline by adsorption process onto granular activated carbon (GAC) is reported from aqueous solutions containing catechol and resorcinol separately. The Taguchi experimental design was applied to study the effect of such parameters as the initial component concentrations (C(0,i)) of two solutes (aniline and catechol or aniline and resorcinol) in the solution, temperature (T), adsorbent dosage (m) and contact time (t). The L27 orthogonal array consisting of five parameters each with three levels was used to determine the total amount of solutes adsorbed on GAC (q(tot), mmol/g) and the signal-to-noise ratio. The analysis of variance (ANOVA) was used to determine the optimum conditions. Under these conditions, the ANOVA shows that m is the most important parameter in the adsorption process. The most favourable levels of process parameters were T = 303 K, m = 10 g/l and t = 660 min for both the systems, qtot values in the confirmation experiments carried out at optimum conditions were 0.73 and 0.95 mmol/g for aniline-catechol and aniline-resorcinol systems, respectively.

Optimization of laser welding thin-gage galvanized steel via response surface methodology

NASA Astrophysics Data System (ADS)

Zhao, Yangyang; Zhang, Yansong; Hu, Wei; Lai, Xinmin

2012-09-01

The increasing demand of light weight and durability makes thin-gage galvanized steels (<0.6 mm) attractive for future automotive applications. Laser welding, well known for its deep penetration, high speed and small heat affected zone, provides a potential solution for welding thin-gage galvanized steels in automotive industry. In this study, the effect of the laser welding parameters (i.e. laser power, welding speed, gap and focal position) on the weld bead geometry (i.e. weld depth, weld width and surface concave) of 0.4 mm-thick galvanized SAE1004 steel in a lap joint configuration has been investigated by experiments. The process windows of the concerned process parameters were therefore determined. Then, response surface methodology (RSM) was used to develop models to predict the relationship between the processing parameters and the laser weld bead profile and identify the correct and optimal combination of the laser welding input variables to obtain superior weld joint. Under the optimal welding parameters, defect-free weld were produced, and the average aspect ratio increased about 30%, from 0.62 to 0.83.

Estimating Soil Hydraulic Parameters using Gradient Based Approach

NASA Astrophysics Data System (ADS)

Rai, P. K.; Tripathi, S.

2017-12-01

The conventional way of estimating parameters of a differential equation is to minimize the error between the observations and their estimates. The estimates are produced from forward solution (numerical or analytical) of differential equation assuming a set of parameters. Parameter estimation using the conventional approach requires high computational cost, setting-up of initial and boundary conditions, and formation of difference equations in case the forward solution is obtained numerically. Gaussian process based approaches like Gaussian Process Ordinary Differential Equation (GPODE) and Adaptive Gradient Matching (AGM) have been developed to estimate the parameters of Ordinary Differential Equations without explicitly solving them. Claims have been made that these approaches can straightforwardly be extended to Partial Differential Equations; however, it has been never demonstrated. This study extends AGM approach to PDEs and applies it for estimating parameters of Richards equation. Unlike the conventional approach, the AGM approach does not require setting-up of initial and boundary conditions explicitly, which is often difficult in real world application of Richards equation. The developed methodology was applied to synthetic soil moisture data. It was seen that the proposed methodology can estimate the soil hydraulic parameters correctly and can be a potential alternative to the conventional method.

A Computational approach in optimizing process parameters of GTAW for SA 106 Grade B steel pipes using Response surface methodology

NASA Astrophysics Data System (ADS)

Sumesh, A.; Sai Ramnadh, L. V.; Manish, P.; Harnath, V.; Lakshman, V.

2016-09-01

Welding is one of the most common metal joining techniques used in industry for decades. As in the global manufacturing scenario the products should be more cost effective. Therefore the selection of right process with optimal parameters will help the industry in minimizing their cost of production. SA 106 Grade B steel has a wide application in Automobile chassis structure, Boiler tubes and pressure vessels industries. Employing central composite design the process parameters for Gas Tungsten Arc Welding was optimized. The input parameters chosen were weld current, peak current and frequency. The joint tensile strength was the response considered in this study. Analysis of variance was performed to determine the statistical significance of the parameters and a Regression analysis was performed to determine the effect of input parameters over the response. From the experiment the maximum tensile strength obtained was 95 KN reported for a weld current of 95 Amp, frequency of 50 Hz and peak current of 100 Amp. With an aim of maximizing the joint strength using Response optimizer a target value of 100 KN is selected and regression models were optimized. The output results are achievable with a Weld current of 62.6148 Amp, Frequency of 23.1821 Hz, and Peak current of 65.9104 Amp. Using Die penetration test the weld joints were also classified in to 2 categories as good weld and weld with defect. This will also help in getting a defect free joint when welding is performed using GTAW process.

[Construction and analysis of a monitoring system with remote real-time multiple physiological parameters based on cloud computing].

PubMed

Zhu, Lingyun; Li, Lianjie; Meng, Chunyan

2014-12-01

There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients' historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in real-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvious advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other issues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a "wearable wireless sensor plus mobile wireless transmission plus cloud computing service" mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

Analyzing parameters optimisation in minimising warpage on side arm using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Rayhana, N.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

This paper presents a systematic methodology to analyse the warpage of the side arm part using Autodesk Moldflow Insight software. Response Surface Methodology (RSM) was proposed to optimise the processing parameters that will result in optimal solutions by efficiently minimising the warpage of the side arm part. The variable parameters considered in this study was based on most significant parameters affecting warpage stated by previous researchers, that is melt temperature, mould temperature and packing pressure while adding packing time and cooling time as these is the commonly used parameters by researchers. The results show that warpage was improved by 10.15% and the most significant parameters affecting warpage are packing pressure.

On the identifiability of inertia parameters of planar Multi-Body Space Systems

NASA Astrophysics Data System (ADS)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.

Application of densification process in organic waste management.

PubMed

Zafari, Abedin; Kianmehr, Mohammad Hossein

2013-07-01

Densification of biomass material that usually has a low density is good way of increasing density, reducing the cost of transportation, and simplifying the storage and distribution of this material. The current study was conducted to investigate the influence of raw material parameters (moisture content and particle size), and densification process parameters (piston speed and die length) on the density and durability of pellets from compost manure. A hydraulic press and a single pelleter were used to produce pellets in controlled conditions. Ground biomass samples were compressed with three levels of moisture content [35%, 40% and 45% (wet basis)], piston speed (2, 6 and 10 mm/s), die length (8, 10 and 12 mm) and particle size (0.3., 0.9 and 1.5 mm) to establish density and durability of pellets. A response surface methodology based on the Box Behnken design was used to study the responses pattern and to understand the influence of parameters. The results revealed that all independent variables have significant (P < 0.01) effects on studied responses in this research.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Digital communications study

NASA Technical Reports Server (NTRS)

Boorstyn, R. R.

1973-01-01

Research is reported dealing with problems of digital data transmission and computer communications networks. The results of four individual studies are presented which include: (1) signal processing with finite state machines, (2) signal parameter estimation from discrete-time observations, (3) digital filtering for radar signal processing applications, and (4) multiple server queues where all servers are not identical.

Study of the Production of a Metallic Coating on Natural Fiber Composite Through the Cold Spray Technique

NASA Astrophysics Data System (ADS)

Astarita, Antonello; Boccarusso, Luca; Durante, Massimo; Viscusi, Antonio; Sansone, Raffaele; Carrino, Luigi

2018-02-01

The deposition of a metallic coating on hemp-PLA (polylactic acid) laminate through the cold spray technique was studied in this paper. A number of different combinations of the deposition parameters were tested to investigate the feasibility of the process. The feasibility of the process was proved when processing conditions are properly set. The bonding mechanism between the substrate and the first layer of particles was studied through scanning electron microscope observations, and it was found that the polymeric matrix experiences a huge plastic deformation to accommodate the impinging particles; conversely a different mechanism was observed when metallic powders impact against a previously deposited metallic layer. The difference between the bonding mechanism and the growth of the coating was also highlighted. Depending on the spraying parameters, four different processing conditions were highlighted and discussed, and as a result the processing window was defined. The mechanical properties of the composite panel before and after the deposition were also investigated. The experiments showed that when properly carried out, the deposition process does not affect the strength of the panel; moreover, no improvements were observed because the contribution of the coating is negligible with respect to one of the reinforcement fibers.

Advanced multivariate data analysis to determine the root cause of trisulfide bond formation in a novel antibody-peptide fusion.

PubMed

Goldrick, Stephen; Holmes, William; Bond, Nicholas J; Lewis, Gareth; Kuiper, Marcel; Turner, Richard; Farid, Suzanne S

2017-10-01

Product quality heterogeneities, such as a trisulfide bond (TSB) formation, can be influenced by multiple interacting process parameters. Identifying their root cause is a major challenge in biopharmaceutical production. To address this issue, this paper describes the novel application of advanced multivariate data analysis (MVDA) techniques to identify the process parameters influencing TSB formation in a novel recombinant antibody-peptide fusion expressed in mammalian cell culture. The screening dataset was generated with a high-throughput (HT) micro-bioreactor system (Ambr TM 15) using a design of experiments (DoE) approach. The complex dataset was firstly analyzed through the development of a multiple linear regression model focusing solely on the DoE inputs and identified the temperature, pH and initial nutrient feed day as important process parameters influencing this quality attribute. To further scrutinize the dataset, a partial least squares model was subsequently built incorporating both on-line and off-line process parameters and enabled accurate predictions of the TSB concentration at harvest. Process parameters identified by the models to promote and suppress TSB formation were implemented on five 7 L bioreactors and the resultant TSB concentrations were comparable to the model predictions. This study demonstrates the ability of MVDA to enable predictions of the key performance drivers influencing TSB formation that are valid also upon scale-up. Biotechnol. Bioeng. 2017;114: 2222-2234. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc. © 2017 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Development and evaluation of paclitaxel nanoparticles using a quality-by-design approach.

PubMed

Yerlikaya, Firat; Ozgen, Aysegul; Vural, Imran; Guven, Olgun; Karaagaoglu, Ergun; Khan, Mansoor A; Capan, Yilmaz

2013-10-01

The aims of this study were to develop and characterize paclitaxel nanoparticles, to identify and control critical sources of variability in the process, and to understand the impact of formulation and process parameters on the critical quality attributes (CQAs) using a quality-by-design (QbD) approach. For this, a risk assessment study was performed with various formulation and process parameters to determine their impact on CQAs of nanoparticles, which were determined to be average particle size, zeta potential, and encapsulation efficiency. Potential risk factors were identified using an Ishikawa diagram and screened by Plackett-Burman design and finally nanoparticles were optimized using Box-Behnken design. The optimized formulation was further characterized by Fourier transform infrared spectroscopy, X-ray diffractometry, differential scanning calorimetry, scanning electron microscopy, atomic force microscopy, and gas chromatography. It was observed that paclitaxel transformed from crystalline state to amorphous state while totally encapsulating into the nanoparticles. The nanoparticles were spherical, smooth, and homogenous with no dichloromethane residue. In vitro cytotoxicity test showed that the developed nanoparticles are more efficient than free paclitaxel in terms of antitumor activity (more than 25%). In conclusion, this study demonstrated that understanding formulation and process parameters with the philosophy of QbD is useful for the optimization of complex drug delivery systems. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Automatic management system for dose parameters in interventional radiology and cardiology.

PubMed

Ten, J I; Fernandez, J M; Vaño, E

2011-09-01

The purpose of this work was to develop an automatic management system to archive and analyse the major study parameters and patient doses for fluoroscopy guided procedures performed in cardiology and interventional radiology systems. The X-ray systems used for this trial have the capability to export at the end of the procedure and via e-mail the technical parameters of the study and the patient dose values. An application was developed to query and retrieve from a mail server, all study reports sent by the imaging modality and store them on a Microsoft SQL Server data base. The results from 3538 interventional study reports generated by 7 interventional systems were processed. In the case of some technical parameters and patient doses, alarms were added to receive malfunction alerts so as to immediately take appropriate corrective actions.

Mathematical form models of tree trunks

Treesearch

Rudolfs Ozolins

2000-01-01

Assortment structure analysis of tree trunks is a characteristic and proper problem that can be solved by using mathematical modeling and standard computer programs. Mathematical form model of tree trunks consists of tapering curve equations and their parameters. Parameters for nine species were obtained by processing measurements of 2,794 model trees and studying the...

Kinetic study of the anaerobic biodegradation of alkyl polyglucosides and the influence of their structural parameters.

PubMed

Ríos, Francisco; Fernández-Arteaga, Alejandro; Lechuga, Manuela; Jurado, Encarnación; Fernández-Serrano, Mercedes

2016-05-01

This paper reports a study of the anaerobic biodegradation of non-ionic surfactants alkyl polyglucosides applying the method by measurement of the biogas production in digested sludge. Three alkyl polyglucosides with different length alkyl chain and degree of polymerization of the glucose units were tested. The influence of their structural parameters was evaluated, and the characteristics parameters of the anaerobic biodegradation were determined. Results show that alkyl polyglucosides, at the standard initial concentration of 100 mgC L(-1), are not completely biodegradable in anaerobic conditions because they inhibit the biogas production. The alkyl polyglucoside having the shortest alkyl chain showed the fastest biodegradability and reached the higher percentage of final mineralization. The anaerobic process was well adjusted to a pseudo first-order equation using the carbon produced as gas during the test; also, kinetics parameters and a global rate constant for all the involved metabolic process were determined. This modeling is helpful to evaluate the biodegradation or the persistence of alkyl polyglucosides under anaerobic conditions in the environment and in the wastewater treatment.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Uncertainty Quantification in Simulations of Epidemics Using Polynomial Chaos

PubMed Central

Santonja, F.; Chen-Charpentier, B.

2012-01-01

Mathematical models based on ordinary differential equations are a useful tool to study the processes involved in epidemiology. Many models consider that the parameters are deterministic variables. But in practice, the transmission parameters present large variability and it is not possible to determine them exactly, and it is necessary to introduce randomness. In this paper, we present an application of the polynomial chaos approach to epidemiological mathematical models based on ordinary differential equations with random coefficients. Taking into account the variability of the transmission parameters of the model, this approach allows us to obtain an auxiliary system of differential equations, which is then integrated numerically to obtain the first-and the second-order moments of the output stochastic processes. A sensitivity analysis based on the polynomial chaos approach is also performed to determine which parameters have the greatest influence on the results. As an example, we will apply the approach to an obesity epidemic model. PMID:22927889

Estimation of forest biomass using remote sensing

NASA Astrophysics Data System (ADS)

Sarker, Md. Latifur Rahman

Forest biomass estimation is essential for greenhouse gas inventories, terrestrial carbon accounting and climate change modelling studies. The availability of new SAR, (C-band RADARSAT-2 and L-band PALSAR) and optical sensors (SPOT-5 and AVNIR-2) has opened new possibilities for biomass estimation because these new SAR sensors can provide data with varying polarizations, incidence angles and fine spatial resolutions. 'Therefore, this study investigated the potential of two SAR sensors (RADARSAT-2 with C-band and PALSAR with L-band) and two optical sensors (SPOT-5 and AVNIR2) for the estimation of biomass in Hong Kong. Three common major processing steps were used for data processing, namely (i) spectral reflectance/intensity, (ii) texture measurements and (iii) polarization or band ratios of texture parameters. Simple linear and stepwise multiple regression models were developed to establish a relationship between the image parameters and the biomass of field plots. The results demonstrate the ineffectiveness of raw data. However, significant improvements in performance (r2) (RADARSAT-2=0.78; PALSAR=0.679; AVNIR-2=0.786; SPOT-5=0.854; AVNIR-2 + SPOT-5=0.911) were achieved using texture parameters of all sensors. The performances were further improved and very promising performances (r2) were obtained using the ratio of texture parameters (RADARSAT-2=0.91; PALSAR=0.823; PALSAR two-date=0.921; AVNIR-2=0.899; SPOT-5=0.916; AVNIR-2 + SPOT-5=0.939). These performances suggest four main contributions arising from this research, namely (i) biomass estimation can be significantly improved by using texture parameters, (ii) further improvements can be obtained using the ratio of texture parameters, (iii) multisensor texture parameters and their ratios have more potential than texture from a single sensor, and (iv) biomass can be accurately estimated far beyond the previously perceived saturation levels of SAR and optical data using texture parameters or the ratios of texture parameters. A further important contribution resulting from the fusion of SAR & optical images produced accuracies (r2) of 0.706 and 0.77 from the simple fusion, and the texture processing of the fused image, respectively. Although these performances were not as attractive as the performances obtained from the other four processing steps, the wavelet fusion procedure improved the saturation level of the optical (AVNIR-2) image very significantly after fusion with SAR, image. Keywords: biomass, climate change, SAR, optical, multisensors, RADARSAT-2, PALSAR, AVNIR-2, SPOT-5, texture measurement, ratio of texture parameters, wavelets, fusion, saturation

X-ray Computed Tomography Assessment of Air Void Distribution in Concrete

NASA Astrophysics Data System (ADS)

Lu, Haizhu

Air void size and spatial distribution have long been regarded as critical parameters in the frost resistance of concrete. In cement-based materials, entrained air void systems play an important role in performance as related to durability, permeability, and heat transfer. Many efforts have been made to measure air void parameters in a more efficient and reliable manner in the past several decades. Standardized measurement techniques based on optical microscopy and stereology on flat cut and polished surfaces are widely used in research as well as in quality assurance and quality control applications. Other more automated methods using image processing have also been utilized, but still starting from flat cut and polished surfaces. The emergence of X-ray computed tomography (CT) techniques provides the capability of capturing the inner microstructure of materials at the micrometer and nanometer scale. X-ray CT's less demanding sample preparation and capability to measure 3D distributions of air voids directly provide ample prospects for its wider use in air void characterization in cement-based materials. However, due to the huge number of air voids that can exist within a limited volume, errors can easily arise in the absence of a formalized data processing procedure. In this study, air void parameters in selected types of cement-based materials (lightweight concrete, structural concrete elements, pavements, and laboratory mortars) have been measured using micro X-ray CT. The focus of this study is to propose a unified procedure for processing the data and to provide solutions to deal with common problems that arise when measuring air void parameters: primarily the reliable segmentation of objects of interest, uncertainty estimation of measured parameters, and the comparison of competing segmentation parameters.

Finite Element Method (FEM) Modeling of Freeze-drying: Monitoring Pharmaceutical Product Robustness During Lyophilization.

PubMed

Chen, Xiaodong; Sadineni, Vikram; Maity, Mita; Quan, Yong; Enterline, Matthew; Mantri, Rao V

2015-12-01

Lyophilization is an approach commonly undertaken to formulate drugs that are unstable to be commercialized as ready to use (RTU) solutions. One of the important aspects of commercializing a lyophilized product is to transfer the process parameters that are developed in lab scale lyophilizer to commercial scale without a loss in product quality. This process is often accomplished by costly engineering runs or through an iterative process at the commercial scale. Here, we are highlighting a combination of computational and experimental approach to predict commercial process parameters for the primary drying phase of lyophilization. Heat and mass transfer coefficients are determined experimentally either by manometric temperature measurement (MTM) or sublimation tests and used as inputs for the finite element model (FEM)-based software called PASSAGE, which computes various primary drying parameters such as primary drying time and product temperature. The heat and mass transfer coefficients will vary at different lyophilization scales; hence, we present an approach to use appropriate factors while scaling-up from lab scale to commercial scale. As a result, one can predict commercial scale primary drying time based on these parameters. Additionally, the model-based approach presented in this study provides a process to monitor pharmaceutical product robustness and accidental process deviations during Lyophilization to support commercial supply chain continuity. The approach presented here provides a robust lyophilization scale-up strategy; and because of the simple and minimalistic approach, it will also be less capital intensive path with minimal use of expensive drug substance/active material.

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for ecosystem carbon cycle studies

Treesearch

Y. He; Q. Zhuang; A.D. McGuire; Y. Liu; M. Chen

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations inmodeling regional carbon dynamics and explore the...

ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

On the interpretation of weight vectors of linear models in multivariate neuroimaging.

PubMed

Haufe, Stefan; Meinecke, Frank; Görgen, Kai; Dähne, Sven; Haynes, John-Dylan; Blankertz, Benjamin; Bießmann, Felix

2014-02-15

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Optimizing friction stir weld parameters of aluminum and copper using conventional milling machine

NASA Astrophysics Data System (ADS)

Manisegaran, Lohappriya V.; Ahmad, Nurainaa Ayuni; Nazri, Nurnadhirah; Noor, Amirul Syafiq Mohd; Ramachandran, Vignesh; Ismail, Muhammad Tarmizizulfika; Ahmad, Ku Zarina Ku; Daruis, Dian Darina Indah

2018-05-01

The joining of two of any particular materials through friction stir welding (FSW) are done by a rotating tool and the work piece material that generates heat which causes the region near the FSW tool to soften. This in return will mechanically intermix the work pieces. The first objective of this study is to join aluminum plates and copper plates by means of friction stir welding process using self-fabricated tools and conventional milling machine. This study also aims to investigate the optimum process parameters to produce the optimum mechanical properties of the welding joints for Aluminum plates and Copper plates. A suitable tool bit and a fixture is to be fabricated for the welding process. A conventional milling machine will be used to weld the aluminum and copper. The most important parameters to enable the process are speed and pressure of the tool (or tool design and alignment of the tool onto the work piece). The study showed that the best surface finish was produced from speed of 1150 rpm and tool bit tilted to 3°. For a 200mm × 100mm Aluminum 6061 with plate thickness of 2 mm at a speed of 1 mm/s, the time taken to complete the welding is only 200 seconds or equivalent to 3 minutes and 20 seconds. The Copper plates was successfully welded using FSW with tool rotation speed of 500 rpm, 700 rpm, 900 rpm, 1150 rpm and 1440 rpm and with welding traverse rate of 30 mm/min, 60 mm/min and 90 mm/min. As the conclusion, FSW using milling machine can be done on both Aluminum and Copper plates, however the weld parameters are different for the two types of plates.

Application of support vector regression for optimization of vibration flow field of high-density polyethylene melts characterized by small angle light scattering

NASA Astrophysics Data System (ADS)

Xian, Guangming

2018-03-01

In this paper, the vibration flow field parameters of polymer melts in a visual slit die are optimized by using intelligent algorithm. Experimental small angle light scattering (SALS) patterns are shown to characterize the processing process. In order to capture the scattered light, a polarizer and an analyzer are placed before and after the polymer melts. The results reported in this study are obtained using high-density polyethylene (HDPE) with rotation speed at 28 rpm. In addition, support vector regression (SVR) analytical method is introduced for optimization the parameters of vibration flow field. This work establishes the general applicability of SVR for predicting the optimal parameters of vibration flow field.

Clinical Parameters and Tools for Home-Based Assessment of Parkinson's Disease: Results from a Delphi study.

PubMed

Ferreira, Joaquim J; Santos, Ana T; Domingos, Josefa; Matthews, Helen; Isaacs, Tom; Duffen, Joy; Al-Jawad, Ahmed; Larsen, Frank; Artur Serrano, J; Weber, Peter; Thoms, Andrea; Sollinger, Stefan; Graessner, Holm; Maetzler, Walter

2015-01-01

Parkinson's disease (PD) is a neurodegenerative disorder with fluctuating symptoms. To aid the development of a system to evaluate people with PD (PwP) at home (SENSE-PARK system) there was a need to define parameters and tools to be applied in the assessment of 6 domains: gait, bradykinesia/hypokinesia, tremor, sleep, balance and cognition. To identify relevant parameters and assessment tools of the 6 domains, from the perspective of PwP, caregivers and movement disorders specialists. A 2-round Delphi study was conducted to select a core of parameters and assessment tools to be applied. This process included PwP, caregivers and movement disorders specialists. Two hundred and thirty-three PwP, caregivers and physicians completed the first round questionnaire, and 50 the second. Results allowed the identification of parameters and assessment tools to be added to the SENSE-PARK system. The most consensual parameters were: Falls and Near Falls; Capability to Perform Activities of Daily Living; Interference with Activities of Daily Living; Capability to Process Tasks; and Capability to Recall and Retrieve Information. The most cited assessment strategies included Walkers; the Evaluation of Performance Doing Fine Motor Movements; Capability to Eat; Assessment of Sleep Quality; Identification of Circumstances and Triggers for Loose of Balance and Memory Assessment. An agreed set of measuring parameters, tests, tools and devices was achieved to be part of a system to evaluate PwP at home. A pattern of different perspectives was identified for each stakeholder.

A Review of Metal Injection Molding- Process, Optimization, Defects and Microwave Sintering on WC-Co Cemented Carbide

NASA Astrophysics Data System (ADS)

Shahbudin, S. N. A.; Othman, M. H.; Amin, Sri Yulis M.; Ibrahim, M. H. I.

2017-08-01

This article is about a review of optimization of metal injection molding and microwave sintering process on tungsten cemented carbide produce by metal injection molding process. In this study, the process parameters for the metal injection molding were optimized using Taguchi method. Taguchi methods have been used widely in engineering analysis to optimize the performance characteristics through the setting of design parameters. Microwave sintering is a process generally being used in powder metallurgy over the conventional method. It has typical characteristics such as accelerated heating rate, shortened processing cycle, high energy efficiency, fine and homogeneous microstructure, and enhanced mechanical performance, which is beneficial to prepare nanostructured cemented carbides in metal injection molding. Besides that, with an advanced and promising technology, metal injection molding has proven that can produce cemented carbides. Cemented tungsten carbide hard metal has been used widely in various applications due to its desirable combination of mechanical, physical, and chemical properties. Moreover, areas of study include common defects in metal injection molding and application of microwave sintering itself has been discussed in this paper.

Effect of pilot-scale aseptic processing on tomato soup quality parameters.

PubMed

Colle, Ines J P; Andrys, Anna; Grundelius, Andrea; Lemmens, Lien; Löfgren, Anders; Buggenhout, Sandy Van; Loey, Ann; Hendrickx, Marc Van

2011-01-01

Tomatoes are often processed into shelf-stable products. However, the different processing steps might have an impact on the product quality. In this study, a model tomato soup was prepared and the impact of pilot-scale aseptic processing, including heat treatment and high-pressure homogenization, on some selected quality parameters was evaluated. The vitamin C content, the lycopene isomer content, and the lycopene bioaccessibility were considered as health-promoting attributes. As a structural characteristic, the viscosity of the tomato soup was investigated. A tomato soup without oil as well as a tomato soup containing 5% olive oil were evaluated. Thermal processing had a negative effect on the vitamin C content, while lycopene degradation was limited. For both compounds, high-pressure homogenization caused additional losses. High-pressure homogenization also resulted in a higher viscosity that was accompanied by a decrease in lycopene bioaccessibility. The presence of lipids clearly enhanced the lycopene isomerization susceptibility and improved the bioaccessibility. The results obtained in this study are of relevance for product formulation and process design of tomato-based food products. © 2011 Institute of Food Technologists®

An Introduction to Data Analysis in Asteroseismology

NASA Astrophysics Data System (ADS)

Campante, Tiago L.

A practical guide is presented to some of the main data analysis concepts and techniques employed contemporarily in the asteroseismic study of stars exhibiting solar-like oscillations. The subjects of digital signal processing and spectral analysis are introduced first. These concern the acquisition of continuous physical signals to be subsequently digitally analyzed. A number of specific concepts and techniques relevant to asteroseismology are then presented as we follow the typical workflow of the data analysis process, namely, the extraction of global asteroseismic parameters and individual mode parameters (also known as peak-bagging) from the oscillation spectrum.

Development of system design information for carbon dioxide using an amine type sorber

NASA Technical Reports Server (NTRS)

Rankin, R. L.; Roehlich, F.; Vancheri, F.

1971-01-01

Development work on system design information for amine type carbon dioxide sorber is reported. Amberlite IR-45, an aminated styrene divinyl benzene matrix, was investigated to determine the influence of design parameters of sorber particle size, process flow rate, CO2 partial pressure, total pressure, and bed designs. CO2 capacity and energy requirements for a 4-man size system were related mathematically to important operational parameters. Some fundamental studies in CO2 sorber capacity, energy requirements, and process operation were also performed.

Parameters of Microcirculation in the Broad Ligament of the Uterus in Wistar Rats after Injection of Autologous Biomedical Cell Product.

PubMed

Dergacheva, T I; Lykov, A P; Shurlygina, A V; Starkova, E V; Poveshchenko, O V; Bondarenko, N A; Kim, I I; Tenditnik, M V; Borodin, Yu I; Konenkov, V I

2015-10-01

We studied the effects of autologous biomedical cell product (bone marrow multipotent mesenchymal stromal cells and their conditioned media) on the parameters of the microcirculatory bed in the broad ligament of the uterus of normal Wistar rats were studied. The parameters of microcirculation and lymph drainage in the broad ligament changed in opposite directions in response to injection of autologous biomedical cell product via different routes. This fact should be taken into consideration when prescribing cell therapy for inflammatory degenerative processes in the pelvic organs.

Parameter inference from hitting times for perturbed Brownian motion.

PubMed

Tamborrino, Massimiliano; Ditlevsen, Susanne; Lansky, Peter

2015-07-01

A latent internal process describes the state of some system, e.g. the social tension in a political conflict, the strength of an industrial component or the health status of a person. When this process reaches a predefined threshold, the process terminates and an observable event occurs, e.g. the political conflict finishes, the industrial component breaks down or the person dies. Imagine an intervention, e.g., a political decision, maintenance of a component or a medical treatment, is initiated to the process before the event occurs. How can we evaluate whether the intervention had an effect? To answer this question we describe the effect of the intervention through parameter changes of the law governing the internal process. Then, the time interval between the start of the process and the final event is divided into two subintervals: the time from the start to the instant of intervention, denoted by S, and the time between the intervention and the threshold crossing, denoted by R. The first question studied here is: What is the joint distribution of (S,R)? The theoretical expressions are provided and serve as a basis to answer the main question: Can we estimate the parameters of the model from observations of S and R and compare them statistically? Maximum likelihood estimators are calculated and applied on simulated data under the assumption that the process before and after the intervention is described by the same type of model, i.e. a Brownian motion, but with different parameters. Also covariates and handling of censored observations are incorporated into the statistical model, and the method is illustrated on lung cancer data.

[Optimize dropping process of Ginkgo biloba dropping pills by using design space approach].

PubMed

Shen, Ji-Chen; Wang, Qing-Qing; Chen, An; Pan, Fang-Lai; Gong, Xing-Chu; Qu, Hai-Bin

2017-07-01

In this paper, a design space approach was applied to optimize the dropping process of Ginkgo biloba dropping pills. Firstly, potential critical process parameters and potential process critical quality attributes were determined through literature research and pre-experiments. Secondly, experiments were carried out according to Box-Behnken design. Then the critical process parameters and critical quality attributes were determined based on the experimental results. Thirdly, second-order polynomial models were used to describe the quantitative relationships between critical process parameters and critical quality attributes. Finally, a probability-based design space was calculated and verified. The verification results showed that efficient production of Ginkgo biloba dropping pills can be guaranteed by operating within the design space parameters. The recommended operation ranges for the critical dropping process parameters of Ginkgo biloba dropping pills were as follows: dropping distance of 5.5-6.7 cm, and dropping speed of 59-60 drops per minute, providing a reference for industrial production of Ginkgo biloba dropping pills. Copyright© by the Chinese Pharmaceutical Association.

Hurst Estimation of Scale Invariant Processes with Stationary Increments and Piecewise Linear Drift

NASA Astrophysics Data System (ADS)

Modarresi, N.; Rezakhah, S.

The characteristic feature of the discrete scale invariant (DSI) processes is the invariance of their finite dimensional distributions by dilation for certain scaling factor. DSI process with piecewise linear drift and stationary increments inside prescribed scale intervals is introduced and studied. To identify the structure of the process, first, we determine the scale intervals, their linear drifts and eliminate them. Then, a new method for the estimation of the Hurst parameter of such DSI processes is presented and applied to some period of the Dow Jones indices. This method is based on fixed number equally spaced samples inside successive scale intervals. We also present some efficient method for estimating Hurst parameter of self-similar processes with stationary increments. We compare the performance of this method with the celebrated FA, DFA and DMA on the simulated data of fractional Brownian motion (fBm).

Mining manufacturing data for discovery of high productivity process characteristics.

PubMed

Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

2010-06-01

Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buchheit, Thomas E.; Wilcox, Ian Zachary; Sandoval, Andrew J

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction andmore » portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.« less

Quantitative assessment of cervical vertebral maturation using cone beam computed tomography in Korean girls.

PubMed

Byun, Bo-Ram; Kim, Yong-Il; Yamaguchi, Tetsutaro; Maki, Koutaro; Son, Woo-Sung

2015-01-01

This study was aimed to examine the correlation between skeletal maturation status and parameters from the odontoid process/body of the second vertebra and the bodies of third and fourth cervical vertebrae and simultaneously build multiple regression models to be able to estimate skeletal maturation status in Korean girls. Hand-wrist radiographs and cone beam computed tomography (CBCT) images were obtained from 74 Korean girls (6-18 years of age). CBCT-generated cervical vertebral maturation (CVM) was used to demarcate the odontoid process and the body of the second cervical vertebra, based on the dentocentral synchondrosis. Correlation coefficient analysis and multiple linear regression analysis were used for each parameter of the cervical vertebrae (P < 0.05). Forty-seven of 64 parameters from CBCT-generated CVM (independent variables) exhibited statistically significant correlations (P < 0.05). The multiple regression model with the greatest R (2) had six parameters (PH2/W2, UW2/W2, (OH+AH2)/LW2, UW3/LW3, D3, and H4/W4) as independent variables with a variance inflation factor (VIF) of <2. CBCT-generated CVM was able to include parameters from the second cervical vertebral body and odontoid process, respectively, for the multiple regression models. This suggests that quantitative analysis might be used to estimate skeletal maturation status.

Review on innovative techniques in oil sludge bioremediation

NASA Astrophysics Data System (ADS)

Mahdi, Abdullah M. El; Aziz, Hamidi Abdul; Eqab, Eqab Sanoosi

2017-10-01

Petroleum hydrocarbon waste is produced in worldwide refineries in significant amount. In Libya, approximately 10,000 tons of oil sludge is generated in oil refineries (hydrocarbon waste mixtures) annually. Insufficient treatment of those wastes can threaten the human health and safety as well as our environment. One of the major challenges faced by petroleum refineries is the safe disposal of oil sludge generated during the cleaning and refining process stages of crude storage facilities. This paper reviews the hydrocarbon sludge characteristics and conventional methods for remediation of oil hydrocarbon from sludge. This study intensively focuses on earlier literature to describe the recently selected innovation technology in oily hydrocarbon sludge bioremediation process. Conventional characterization parameters or measurable factors can be gathered in chemical, physical, and biological parameters: (1) Chemical parameters are consequently necessary in the case of utilization of topsoil environment when they become relevant to the presence of nutrients and toxic compounds; (2) Physical parameters provide general data on sludge process and hand ability; (3) Biological parameters provide data on microbial activity and organic matter presence, which will be used to evaluate the safety of the facilities. The objective of this research is to promote the bioremediating oil sludge feasibility from Marsa El Hariga Terminal and Refinery (Tobruk).

Evaluation of the AnnAGNPS Model for Predicting Runoff and Nutrient Export in a Typical Small Watershed in the Hilly Region of Taihu Lake.

PubMed

Luo, Chuan; Li, Zhaofu; Li, Hengpeng; Chen, Xiaomin

2015-09-02

The application of hydrological and water quality models is an efficient approach to better understand the processes of environmental deterioration. This study evaluated the ability of the Annualized Agricultural Non-Point Source (AnnAGNPS) model to predict runoff, total nitrogen (TN) and total phosphorus (TP) loading in a typical small watershed of a hilly region near Taihu Lake, China. Runoff was calibrated and validated at both an annual and monthly scale, and parameter sensitivity analysis was performed for TN and TP before the two water quality components were calibrated. The results showed that the model satisfactorily simulated runoff at annual and monthly scales, both during calibration and validation processes. Additionally, results of parameter sensitivity analysis showed that the parameters Fertilizer rate, Fertilizer organic, Canopy cover and Fertilizer inorganic were more sensitive to TN output. In terms of TP, the parameters Residue mass ratio, Fertilizer rate, Fertilizer inorganic and Canopy cover were the most sensitive. Based on these sensitive parameters, calibration was performed. TN loading produced satisfactory results for both the calibration and validation processes, whereas the performance of TP loading was slightly poor. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for the planning and management of watersheds.

Determination of melt pool dimensions using DOE-FEM and RSM with process window during SLM of Ti6Al4V powder

NASA Astrophysics Data System (ADS)

Zhuang, Jyun-Rong; Lee, Yee-Ting; Hsieh, Wen-Hsin; Yang, An-Shik

2018-07-01

Selective laser melting (SLM) shows a positive prospect as an additive manufacturing (AM) technique for fabrication of 3D parts with complicated structures. A transient thermal model was developed by the finite element method (FEM) to simulate the thermal behavior for predicting the time evolution of temperature field and melt pool dimensions of Ti6Al4V powder during SLM. The FEM predictions were then compared with published experimental measurements and calculation results for model validation. This study applied the design of experiment (DOE) scheme together with the response surface method (RSM) to conduct the regression analysis based on four processing parameters (exactly, the laser power, scanning speed, preheating temperature and hatch space) for predicting the dimensions of the melt pool in SLM. The preliminary RSM results were used to quantify the effects of those parameters on the melt pool size. The process window was further implemented via two criteria of the width and depth of the molten pool to screen impractical conditions of four parameters for including the practical ranges of processing parameters. The FEM simulations confirmed the good accuracy of the critical RSM models in the predictions of melt pool dimensions for three typical SLM working scenarios.

Optimization of drug loading to improve physical stability of paclitaxel-loaded long-circulating liposomes.

PubMed

Kannan, Vinayagam; Balabathula, Pavan; Divi, Murali K; Thoma, Laura A; Wood, George C

2015-01-01

The effect of formulation and process parameters on drug loading and physical stability of paclitaxel-loaded long-circulating liposomes was evaluated. The liposomes were prepared by hydration-extrusion method. The formulation parameters such as total lipid content, cholesterol content, saturated-unsaturated lipid ratio, drug-lipid ratio and process parameters such as extrusion pressure and number of extrusion cycles were studied and their impact on drug loading and physical stability was evaluated. A proportionate increase in drug loading was observed with increase in the total phospholipid content. Cholesterol content and saturated lipid content in the bilayer showed a negative influence on drug loading. The short-term stability evaluation of liposomes prepared with different drug-lipid ratios demonstrated that 1:60 as the optimum drug-lipid ratio to achieve a loading of 1-1.3 mg/mL without the risk of physical instability. The vesicle size decreased with an increase in the extrusion pressure and number of extrusion cycles, but no significant trends were observed for drug loading with changes in process pressure or number of cycles. The optimization of formulation and process parameters led to a physically stable formulation of paclitaxel-loaded long-circulating liposomes that maintain size, charge and integrity during storage.

Localised anodic oxidation of aluminium material using a continuous electrolyte jet

NASA Astrophysics Data System (ADS)

Kuhn, D.; Martin, A.; Eckart, C.; Sieber, M.; Morgenstern, R.; Hackert-Oschätzchen, M.; Lampke, T.; Schubert, A.

2017-03-01

Anodic oxidation of aluminium and its alloys is often used as protection against material wearout and corrosion. Therefore, anodic oxidation of aluminium is applied to produce functional oxide layers. The structure and properties of the oxide layers can be influenced by various factors. These factors include for example the properties of the substrate material, like alloy elements and heat treatment or process parameters, like operating temperature, electric parameters or the type of the used electrolyte. In order to avoid damage to the work-piece surface caused by covering materials in masking applications, to minimize the use of resources and to modify the surface in a targeted manner, the anodic oxidation has to be localised to partial areas. Within this study a proper alternative without preparing the substrate by a mask is investigated for generating locally limited anodic oxidation by using a continuous electrolyte jet. Therefore aluminium material EN AW 7075 is machined by applying a continuous electrolyte jet of oxalic acid. Experiments were carried out by varying process parameters like voltage or processing time. The realised oxide spots on the aluminium surface were investigated by optical microscopy, SEM and EDX line scanning. Furthermore, the dependencies of the oxide layer properties from the process parameters are shown.

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

Development of lithium diffused radiation resistant solar cells, part 2

NASA Technical Reports Server (NTRS)

Payne, P. R.; Somberg, H.

1971-01-01

The work performed to investigate the effect of various process parameters on the performance of lithium doped P/N solar cells is described. Effort was concentrated in four main areas: (1) the starting material, (2) the boron diffusion, (3) the lithium diffusion, and (4) the contact system. Investigation of starting material primarily involved comparison of crucible grown silicon (high oxygen content) and Lopex silicon (low oxygen content). In addition, the effect of varying growing parameters of crucible grown silicon on lithium cell output was also examined. The objective of the boron diffusion studies was to obtain a diffusion process which produced high efficiency cells with minimal silicon stressing and could be scaled up to process 100 or more cells per diffusion. Contact studies included investigating sintering of the TiAg contacts and evaluation of the contact integrity.

Analysis of flow field characteristics in IC equipment chamber based on orthogonal design

NASA Astrophysics Data System (ADS)

Liu, W. F.; Yang, Y. Y.; Wang, C. N.

2017-01-01

This paper aims to study the influence of the configuration of processing chamber as a part of IC equipment on flow field characteristics. Four parameters, including chamber height, chamber diameter, inlet mass flow rate and outlet area, are arranged using orthogonally design method to study their influence on flow distribution in the processing chamber with the commercial software-Fluent. The velocity, pressure and temperature distribution above the holder were analysed respectively. The velocity difference value of the gas flow above the holder is defined as the evaluation criteria to evaluate the uniformity of the gas flow. The quantitative relationship between key parameters and the uniformity of gas flow was found through analysis of experimental results. According to our study, the chamber height is the most significant factor, and then follows the outlet area, chamber diameter and inlet mass flow rate. This research can provide insights into the study and design of configuration of etcher, plasma enhanced chemical vapor deposition (PECVD) equipment, and other systems with similar configuration and processing condition.

Extended study on the influence of z-value(s) of single and multicomponent time-temperature integrators on the accuracy of quantitative thermal process assessment.

PubMed

Guiavarc'h, Yann P; van Loey, Ann M; Hendrickx, Marc E

2005-02-01

The possibilities and limitations of single- and multicomponent time-temperature integrators (TTIs) for evaluating the impact of thermal processes on a target food attribute with a Ztarget value different from the zTTI value(s) of the TTI is far from sufficiently documented. In this study, several thousand time-temperature profiles were generated by heat transfer simulations based on a wide range of product and process thermal parameters and considering a Ztarget value of 10 degrees C and a reference temperature of 121.1 degrees C, both currently used to assess the safety of food sterilization processes. These simulations included 15 different Ztarget=10 degrees CF121.1 degrees C values in the range 3 to 60 min. The integration of the time-temperature profiles with ZTTI values of 5.5 to 20.5 degrees C in steps of 1 degrees C allowed generation of a large database containing for each combination of product and process parameters the correction factor to apply to the process value FmultiTTI, which was derived from a single- or multicomponent TTI, to obtain the target process value 10 degrees CF121.1 degrees C. The table and the graph results clearly demonstrated that multicomponent TTIs with z-values close to 10 degrees C can be used as an extremely efficient approach when a single-component TTI with a z-value of 10 degrees C is not available. In particular, a two-component TTI with z1 and z2 values respectively above and below the Ztarget value (10 degrees C in this study) would be the best option for the development of a TTI to assess the safety of sterilized foods. Whatever process and product parameters are used, such a TTI allows proper evaluation of the process value 10 degrees CF121.1 degrees C.

Numerical simulation of heat transfer and phase change during freezing of potatoes with different shapes at the presence or absence of ultrasound irradiation

NASA Astrophysics Data System (ADS)

Kiani, Hossein; Sun, Da-Wen

2018-03-01

As novel processes such as ultrasound assisted heat transfer are emerged, new models and simulations are needed to describe these processes. In this paper, a numerical model was developed to study the freezing process of potatoes. Different thermal conductivity models were investigated, and the effect of sonication was evaluated on the convective heat transfer in a fluid to the particle heat transfer system. Potato spheres and sticks were the geometries researched, and the effect of different processing parameters on the results were studied. The numerical model successfully predicted the ultrasound assisted freezing of various shapes in comparison with experimental data of the process. The model was sensitive to processing parameters variation (sound intensity, duty cycle, shape, etc.) and could accurately simulate the freezing process. Among the thermal conductivity correlations studied, de Vries and Maxwell models gave closer estimations. The maximum temperature difference was obtained for the series equation that underestimated the thermal conductivity. Both numerical and experimental data confirmed that an optimum condition of intensity and duty cycle is needed for reducing the freezing time, as increasing the intensity, increased the heat transfer rate and sonically heating rate, simultaneously, that acted against each other.

Impact of initial surface parameters on the final quality of laser micro-polished surfaces

NASA Astrophysics Data System (ADS)

Chow, Michael; Bordatchev, Evgueni V.; Knopf, George K.

2012-03-01

Laser micro-polishing (LμP) is a new laser-based microfabrication technology for improving surface quality during a finishing operation and for producing parts and surfaces with near-optical surface quality. The LμP process uses low power laser energy to melt a thin layer of material on the previously machined surface. The polishing effect is achieved as the molten material in the laser-material interaction zone flows from the elevated regions to the local minimum due to surface tension. This flow of molten material then forms a thin ultra-smooth layer on the top surface. The LμP is a complex thermo-dynamic process where the melting, flow and redistribution of molten material is significantly influenced by a variety of process parameters related to the laser, the travel motions and the material. The goal of this study is to analyze the impact of initial surface parameters on the final surface quality. Ball-end micromilling was used for preparing initial surface of samples from H13 tool steel that were polished using a Q-switched Nd:YAG laser. The height and width of micromilled scallops (waviness) were identified as dominant parameter affecting the quality of the LμPed surface. By adjusting process parameters, the Ra value of a surface, having a waviness period of 33 μm and a peak-to-valley value of 5.9 μm, was reduced from 499 nm to 301 nm, improving the final surface quality by 39.7%.

Development of numerical processing in children with typical and dyscalculic arithmetic skills—a longitudinal study

PubMed Central

Landerl, Karin

2013-01-01

Numerical processing has been demonstrated to be closely associated with arithmetic skills, however, our knowledge on the development of the relevant cognitive mechanisms is limited. The present longitudinal study investigated the developmental trajectories of numerical processing in 42 children with age-adequate arithmetic development and 41 children with dyscalculia over a 2-year period from beginning of Grade 2, when children were 7; 6 years old, to beginning of Grade 4. A battery of numerical processing tasks (dot enumeration, non-symbolic and symbolic comparison of one- and two-digit numbers, physical comparison, number line estimation) was given five times during the study (beginning and middle of each school year). Efficiency of numerical processing was a very good indicator of development in numerical processing while within-task effects remained largely constant and showed low long-term stability before middle of Grade 3. Children with dyscalculia showed less efficient numerical processing reflected in specifically prolonged response times. Importantly, they showed consistently larger slopes for dot enumeration in the subitizing range, an untypically large compatibility effect when processing two-digit numbers, and they were consistently less accurate in placing numbers on a number line. Thus, we were able to identify parameters that can be used in future research to characterize numerical processing in typical and dyscalculic development. These parameters can also be helpful for identification of children who struggle in their numerical development. PMID:23898310

Advanced oxidation of Reactive Blue 181 solution: a comparison between Fenton and Sono-Fenton process.

PubMed

Basturk, Emine; Karatas, Mustafa

2014-09-01

In this work, the decolorization of C.I. Reactive Blue 181 (RB181), an anthraquinone dye, by Ultrasound and Fe(2+) H2O2 processes was investigated. The effects of operating parameters, such as Fe(2+) dosage, H2O2 dosage, pH value, reaction time and temperature were examined. Process optimisation [pH, ferrous ion (Fe(2+)), hydrogen peroxide (H2O2), and reaction time], kinetic studies and their comparison were carried out for both of the processes. The Sono-Fenton process was performed by indirect sonication in an ultrasonic water bath, which was operated at a fixed 35-kHz frequency. The optimum conditions were determined as [Fe(2+)]=30 mg/L, [H2O2]=50 mg/L and pH=3 for the Fenton process and [Fe(2+)]=10 mg/L, [H2O2]=40 mg/L and pH=3 for the Sono-Fenton process. The colour removals were 88% and 93.5% by the Fenton and Sono-Fenton processes, respectively. The highest decolorization was achieved by the Sono-Fenton process because of the production of some oxidising agents as a result of sonication. The paper also discussed kinetic parameters. The decolorization kinetic of RB181 followed pseudo-second-order reaction (Fenton study) and Behnajady kinetics (Sono-Fenton study). Copyright © 2014 Elsevier B.V. All rights reserved.

Degradation of edible oil during food processing by ultrasound: electron paramagnetic resonance, physicochemical, and sensory appreciation.

PubMed

Pingret, Daniella; Durand, Grégory; Fabiano-Tixier, Anne-Sylvie; Rockenbauer, Antal; Ginies, Christian; Chemat, Farid

2012-08-08

During ultrasound processing of lipid-containing food, some off-flavors can be detected, which can incite depreciation by consumers. The impacts of ultrasound treatment on sunflower oil using two different ultrasound horns (titanium and pyrex) were evaluated. An electron paramagnetic resonance study was performed to identify and quantify the formed radicals, along with the assessment of classical physicochemical parameters such as peroxide value, acid value, anisidine value, conjugated dienes, polar compounds, water content, polymer quantification, fatty acid composition, and volatiles profile. The study shows an increase of formed radicals in sonicated oils, as well as the modification of physicochemical parameters evidencing an oxidation of treated oils.

Radar systems for the water resources mission, volume 1

NASA Technical Reports Server (NTRS)

Moore, R. K.; Claassen, J. P.; Erickson, R. L.; Fong, R. K. T.; Hanson, B. C.; Komen, M. J.; Mcmillan, S. B.; Parashar, S. K.

1976-01-01

The state of the art determination was made for radar measurement of: soil moisture, snow, standing and flowing water, lake and river ice, determination of required spacecraft radar parameters, study of synthetic-aperture radar systems to meet these parametric requirements, and study of techniques for on-board processing of the radar data. Significant new concepts developed include the following: scanning synthetic-aperture radar to achieve wide-swath coverage; single-sideband radar; and comb-filter range-sequential, range-offset SAR processing. The state of the art in radar measurement of water resources parameters is outlined. The feasibility for immediate development of a spacecraft water resources SAR was established. Numerous candidates for the on-board processor were examined.

Study on the Carbonation Behavior of Cement Mortar by Electrochemical Impedance Spectroscopy

PubMed Central

Dong, Biqin; Qiu, Qiwen; Xiang, Jiaqi; Huang, Canjie; Xing, Feng; Han, Ningxu

2014-01-01

A new electrochemical model has been carefully established to explain the carbonation behavior of cement mortar, and the model has been validated by the experimental results. In fact, it is shown by this study that the electrochemical impedance behavior of mortars varies in the process of carbonation. With the cement/sand ratio reduced, the carbonation rate reveals more remarkable. The carbonation process can be quantitatively accessed by a parameter, which can be obtained by means of the electrochemical impedance spectroscopy (EIS)-based electrochemical model. It has been found that the parameter is a function of carbonation depth and of carbonation time. Thereby, prediction of carbonation depth can be achieved. PMID:28788452

Study on the Carbonation Behavior of Cement Mortar by Electrochemical Impedance Spectroscopy.

PubMed

Dong, Biqin; Qiu, Qiwen; Xiang, Jiaqi; Huang, Canjie; Xing, Feng; Han, Ningxu

2014-01-03

A new electrochemical model has been carefully established to explain the carbonation behavior of cement mortar, and the model has been validated by the experimental results. In fact, it is shown by this study that the electrochemical impedance behavior of mortars varies in the process of carbonation. With the cement/sand ratio reduced, the carbonation rate reveals more remarkable. The carbonation process can be quantitatively accessed by a parameter, which can be obtained by means of the electrochemical impedance spectroscopy (EIS)-based electrochemical model. It has been found that the parameter is a function of carbonation depth and of carbonation time. Thereby, prediction of carbonation depth can be achieved.

Self-tuning regulator for an interacting CSTR process

NASA Astrophysics Data System (ADS)

Rajendra Mungale, Niraj; Upadhyay, Akshay; Jaganatha Pandian, B.

2017-11-01

In the paper we have laid emphasis on STR that is Self Tuning Regulator and its application for an interacting process. CSTR has a great importance in Chemical Process when we deal with controlling different parameters of a process using CSTR. Basically CSTR is used to maintain a constant liquid temperature in the process. The proposed method called self-tuning regulator, is a different scheme where process parameters are updated and the controller parameters are obtained from the solution of a design problem. The paper deals with STR and methods associated with it.

Modeling the UO2 ex-AUC pellet process and predicting the fuel rod temperature distribution under steady-state operating condition

NASA Astrophysics Data System (ADS)

Hung, Nguyen Trong; Thuan, Le Ba; Thanh, Tran Chi; Nhuan, Hoang; Khoai, Do Van; Tung, Nguyen Van; Lee, Jin-Young; Jyothi, Rajesh Kumar

2018-06-01

Modeling uranium dioxide pellet process from ammonium uranyl carbonate - derived uranium dioxide powder (UO2 ex-AUC powder) and predicting fuel rod temperature distribution were reported in the paper. Response surface methodology (RSM) and FRAPCON-4.0 code were used to model the process and to predict the fuel rod temperature under steady-state operating condition. Fuel rod design of AP-1000 designed by Westinghouse Electric Corporation, in these the pellet fabrication parameters are from the study, were input data for the code. The predictive data were suggested the relationship between the fabrication parameters of UO2 pellets and their temperature image in nuclear reactor.

Powder Bed Layer Characteristics: The Overseen First-Order Process Input

NASA Astrophysics Data System (ADS)

Mindt, H. W.; Megahed, M.; Lavery, N. P.; Holmes, M. A.; Brown, S. G. R.

2016-08-01

Powder Bed Additive Manufacturing offers unique advantages in terms of manufacturing cost, lot size, and product complexity compared to traditional processes such as casting, where a minimum lot size is mandatory to achieve economic competitiveness. Many studies—both experimental and numerical—are dedicated to the analysis of how process parameters such as heat source power, scan speed, and scan strategy affect the final material properties. Apart from the general urge to increase the build rate using thicker powder layers, the coating process and how the powder is distributed on the processing table has received very little attention to date. This paper focuses on the first step of every powder bed build process: Coating the process table. A numerical study is performed to investigate how powder is transferred from the source to the processing table. A solid coating blade is modeled to spread commercial Ti-6Al-4V powder. The resulting powder layer is analyzed statistically to determine the packing density and its variation across the processing table. The results are compared with literature reports using the so-called "rain" models. A parameter study is performed to identify the influence of process table displacement and wiper velocity on the powder distribution. The achieved packing density and how that affects subsequent heat source interaction with the powder bed is also investigated numerically.

Development of a Premium Quality Plasma-derived IVIg (IQYMUNE®) Utilizing the Principles of Quality by Design-A Worked-through Case Study.

PubMed

Paolantonacci, Philippe; Appourchaux, Philippe; Claudel, Béatrice; Ollivier, Monique; Dennett, Richard; Siret, Laurent

2018-01-01

Polyvalent human normal immunoglobulins for intravenous use (IVIg), indicated for rare and often severe diseases, are complex plasma-derived protein preparations. A quality by design approach has been used to develop the Laboratoire Français du Fractionnement et des Biotechnologies new-generation IVIg, targeting a high level of purity to generate an enhanced safety profile while maintaining a high level of efficacy. A modular approach of quality by design was implemented consisting of five consecutive steps to cover all the stages from the product design to the final product control strategy.A well-defined target product profile was translated into 27 product quality attributes that formed the basis of the process design. In parallel, a product risk analysis was conducted and identified 19 critical quality attributes among the product quality attributes. Process risk analysis was carried out to establish the links between process parameters and critical quality attributes. Twelve critical steps were identified, and for each of these steps a risk mitigation plan was established.Among the different process risk mitigation exercises, five process robustness studies were conducted at qualified small scale with a design of experiment approach. For each process step, critical process parameters were identified and, for each critical process parameter, proven acceptable ranges were established. The quality risk management and risk mitigation outputs, including verification of proven acceptable ranges, were used to design the process verification exercise at industrial scale.Finally, the control strategy was established using a mix, or hybrid, of the traditional approach plus elements of the quality by design enhanced approach, as illustrated, to more robustly assign material and process controls and in order to securely meet product specifications.The advantages of this quality by design approach were improved process knowledge for industrial design and process validation and a clear justification of the process and product specifications as a basis for control strategy and future comparability exercises. © PDA, Inc. 2018.

Optimization of the dressing parameters in cylindrical grinding based on a generalized utility function

NASA Astrophysics Data System (ADS)

Aleksandrova, Irina

2016-01-01

The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type ??32 and ??80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions (dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility function has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing parameters.

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

PubMed

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.

The Influence of Formulation and Manufacturing Process Parameters on the Characteristics of Lyophilized Orally Disintegrating Tablets

PubMed Central

Jones, Rhys J.; Rajabi-Siahboomi, Ali; Levina, Marina; Perrie, Yvonne; Mohammed, Afzal R.

2011-01-01

Gelatin is a principal excipient used as a binder in the formulation of lyophilized orally disintegrating tablets. The current study focuses on exploiting the physicochemical properties of gelatin by varying formulation parameters to determine their influence on orally disintegrating tablet (ODT) characteristics. Process parameters, namely pH and ionic strength of the formulations, and ball milling were investigated to observe their effects on excipient characteristics and tablet formation. The properties and characteristics of the formulations and tablets which were investigated included: glass transition temperature, wettability, porosity, mechanical properties, disintegration time, morphology of the internal structure of the freeze-dried tablets, and drug dissolution. The results from the pH study revealed that adjusting the pH of the formulation away from the isoelectric point of gelatin, resulted in an improvement in tablet disintegration time possibly due to increase in gelatin swelling resulting in greater tablet porosity. The results from the ionic strength study revealed that the inclusion of sodium chloride influenced tablet porosity, tablet morphology and the glass transition temperature of the formulations. Data from the milling study showed that milling the excipients influenced formulation characteristics, namely wettability and powder porosity. The study concludes that alterations of simple parameters such as pH and salt concentration have a significant influence on formulation of ODT. PMID:24310589

Evaluation of Control Parameters for the Activated Sludge Process

ERIC Educational Resources Information Center

Stall, T. Ray; Sherrard, Josephy H.

1978-01-01

An evaluation of the use of the parameters currently being used to design and operate the activated sludge process is presented. The advantages and disadvantages for the use of each parameter are discussed. (MR)

Case study: Optimizing fault model input parameters using bio-inspired algorithms

NASA Astrophysics Data System (ADS)

Plucar, Jan; Grunt, Onřej; Zelinka, Ivan

2017-07-01

We present a case study that demonstrates a bio-inspired approach in the process of finding optimal parameters for GSM fault model. This model is constructed using Petri Nets approach it represents dynamic model of GSM network environment in the suburban areas of Ostrava city (Czech Republic). We have been faced with a task of finding optimal parameters for an application that requires high amount of data transfers between the application itself and secure servers located in datacenter. In order to find the optimal set of parameters we employ bio-inspired algorithms such as Differential Evolution (DE) or Self Organizing Migrating Algorithm (SOMA). In this paper we present use of these algorithms, compare results and judge their performance in fault probability mitigation.

Oxidizing of ferulic acid with the use of polyoxometalates as catalysts

NASA Astrophysics Data System (ADS)

Povarnitsyna, T. V.; Popova, N. R.; Bogolitsyn, K. G.; Beloglazova, A. L.; Pryakhin, A. N.; Lunin, V. V.

2010-12-01

The kinetics of catalytic oxidation for ferulic acid with polyoxometalates used as catalysts was studied. The effect of pH and concentrations of the principal reacting components on the process kinetics was studied. A kinetic scheme of oxidation is proposed, and the values of a number of kinetic parameters of the process are determined.

Plackett-Burman experimental design for bacterial cellulose-silica composites synthesis.

PubMed

Guzun, Anicuta Stoica; Stroescu, Marta; Jinga, Sorin Ion; Voicu, Georgeta; Grumezescu, Alexandru Mihai; Holban, Alina Maria

2014-09-01

Bacterial cellulose-silica hybrid composites were prepared starting from wet bacterial cellulose (BC) membranes using Stöber reaction. The structure and surface morphology of hybrid composites were examined by FTIR and SEM. The SEM pictures revealed that the silica particles are attached to BC fibrils and are well dispersed in the BC matrix. The influence of silica particles upon BC crystallinity was studied using XRD analysis. Thermogravimetric (TG) analysis showed that the composites are stable up to 300°C. A Plackett-Burman design was applied in order to investigate the influence of process parameters upon silica particle sizes and silica content of BC-silica composites. The statistical model predicted that it is possible for silica particles size to vary the synthesis parameters in order to obtain silica particles deposed on BC membranes in the range from 34.5 to 500 nm, the significant parameters being ammonia concentration, reaction time and temperature. The silica content also varies depending on process parameters, the statistical model predicting that the most influential parameters are water-tetraethoxysilane (TEOS) ratio and reaction temperature. The antimicrobial behavior on Staphylococcus aureus of BC-silica composites functionalized with usnic acid (UA) was also studied, in order to create improved surfaces with antiadherence and anti-biofilm properties. Copyright © 2014 Elsevier B.V. All rights reserved.

Holographic thermalization and generalized Vaidya-AdS solutions in massive gravity

NASA Astrophysics Data System (ADS)

Hu, Ya-Peng; Zeng, Xiao-Xiong; Zhang, Hai-Qing

2017-02-01

We investigate the effect of massive graviton on the holographic thermalization process. Before doing this, we first find out the generalized Vaidya-AdS solutions in the de Rham-Gabadadze-Tolley (dRGT) massive gravity by directly solving the gravitational equations. Then, we study the thermodynamics of these Vaidya-AdS solutions by using the Misner-Sharp energy and unified first law, which also shows that the massive gravity is in a thermodynamic equilibrium state. Moreover, we adopt the two-point correlation function at equal time to explore the thermalization process in the dual field theory, and to see how the graviton mass parameter affects this process from the viewpoint of AdS/CFT correspondence. Our results show that the graviton mass parameter will increase the holographic thermalization process.

In-flight performance of pulse-processing system of the ASTRO-H/Hitomi soft x-ray spectrometer

NASA Astrophysics Data System (ADS)

Ishisaki, Yoshitaka; Yamada, Shinya; Seta, Hiromi; Tashiro, Makoto S.; Takeda, Sawako; Terada, Yukikatsu; Kato, Yuka; Tsujimoto, Masahiro; Koyama, Shu; Mitsuda, Kazuhisa; Sawada, Makoto; Boyce, Kevin R.; Chiao, Meng P.; Watanabe, Tomomi; Leutenegger, Maurice A.; Eckart, Megan E.; Porter, Frederick Scott; Kilbourne, Caroline Anne

2018-01-01

We summarize results of the initial in-orbit performance of the pulse shape processor (PSP) of the soft x-ray spectrometer instrument onboard ASTRO-H (Hitomi). Event formats, kind of telemetry, and the pulse-processing parameters are described, and the parameter settings in orbit are listed. The PSP was powered-on 2 days after launch, and the event threshold was lowered in orbit. The PSP worked fine in orbit, and there was neither memory error nor SpaceWire communication error until the break-up of spacecraft. Time assignment, electrical crosstalk, and the event screening criteria are studied. It is confirmed that the event processing rate at 100% central processing unit load is ˜200 c / s / array, compliant with the requirement on the PSP.

Development of an aerosol microphysical module: Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS)

NASA Astrophysics Data System (ADS)

Matsui, H.; Koike, M.; Kondo, Y.; Fast, J. D.; Takigawa, M.

2014-09-01

Number concentrations, size distributions, and mixing states of aerosols are essential parameters for accurate estimations of aerosol direct and indirect effects. In this study, we develop an aerosol module, designated the Aerosol Two-dimensional bin module for foRmation and Aging Simulation (ATRAS), that can explicitly represent these parameters by considering new particle formation (NPF), black carbon (BC) aging, and secondary organic aerosol (SOA) processes. A two-dimensional bin representation is used for particles with dry diameters from 40 nm to 10 μm to resolve both aerosol sizes (12 bins) and BC mixing states (10 bins) for a total of 120 bins. The particles with diameters between 1 and 40 nm are resolved using additional eight size bins to calculate NPF. The ATRAS module is implemented in the WRF-Chem model and applied to examine the sensitivity of simulated mass, number, size distributions, and optical and radiative parameters of aerosols to NPF, BC aging, and SOA processes over East Asia during the spring of 2009. The BC absorption enhancement by coating materials is about 50% over East Asia during the spring, and the contribution of SOA processes to the absorption enhancement is estimated to be 10-20% over northern East Asia and 20-35% over southern East Asia. A clear north-south contrast is also found between the impacts of NPF and SOA processes on cloud condensation nuclei (CCN) concentrations: NPF increases CCN concentrations at higher supersaturations (smaller particles) over northern East Asia, whereas SOA increases CCN concentrations at lower supersaturations (larger particles) over southern East Asia. The application of ATRAS in East Asia also shows that the impact of each process on each optical and radiative parameter depends strongly on the process and the parameter in question. The module can be used in the future as a benchmark model to evaluate the accuracy of simpler aerosol models and examine interactions between NPF, BC aging, and SOA processes under different meteorological conditions and emissions.

A quality by design approach to understand formulation and process variability in pharmaceutical melt extrusion processes.

PubMed

Patwardhan, Ketaki; Asgarzadeh, Firouz; Dassinger, Thomas; Albers, Jessica; Repka, Michael A

2015-05-01

In this study, the principles of quality by design (QbD) have been uniquely applied to a pharmaceutical melt extrusion process for an immediate release formulation with a low melting model drug, ibuprofen. Two qualitative risk assessment tools - Fishbone diagram and failure mode effect analysis - were utilized to strategically narrow down the most influential parameters. Selected variables were further assessed using a Plackett-Burman screening study, which was upgraded to a response surface design consisting of the critical factors to study the interactions between the study variables. In process torque, glass transition temperature (Tg ) of the extrudates, assay, dissolution and phase change were measured as responses to evaluate the critical quality attributes (CQAs) of the extrudates. The effect of each study variable on the measured responses was analysed using multiple regression for the screening design and partial least squares for the optimization design. Experimental limits for formulation and process parameters to attain optimum processing have been outlined. A design space plot describing the domain of experimental variables within which the CQAs remained unchanged was developed. A comprehensive approach for melt extrusion product development based on the QbD methodology has been demonstrated. Drug loading concentrations between 40- 48%w/w and extrusion temperature in the range of 90-130°C were found to be the most optimum. © 2015 Royal Pharmaceutical Society.

The Parameter of Aspect in Second Language Acquisition.

ERIC Educational Resources Information Center

Slabakova, Roumyana

1999-01-01

Presents a detailed study of the second-language (L2) acquisition of English aspect by native speakers of Slavic languages. Results bring new evidence to bear on the theoretical choice between direct access to the L2 value or starting out the process of acquisition with the first-language value of a parameter, supporting the latter view.…

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Research on tool wearing on milling of TC21 titanium alloy

NASA Astrophysics Data System (ADS)

Guilin, Liu

2017-06-01

Titanium alloys are used in aircraft widely, but the efficiency is a problem for machining titanium alloy. In this paper, the cutting experiment of TC21 titanium alloy was studied. Cutting parameters and test methods for TC21 titanium alloy were designed. The wear behavior of TC21 titanium alloy was studied based on analysis of orthogonal test results. It provides a group of cutting parameters for TC21 titanium alloy processing.

Effects of Process Parameters and Cryotreated Electrode on the Radial Overcut of Aisi 304 IN SiC Powder Mixed Edm

NASA Astrophysics Data System (ADS)

Bhaumik, Munmun; Maity, Kalipada

Powder mixed electro discharge machining (PMEDM) is further advancement of conventional electro discharge machining (EDM) where the powder particles are suspended in the dielectric medium to enhance the machining rate as well as surface finish. Cryogenic treatment is introduced in this process for improving the tool life and cutting tool properties. In the present investigation, the characterization of the cryotreated tempered electrode was performed. An attempt has been made to study the effect of cryotreated double tempered electrode on the radial overcut (ROC) when SiC powder is mixed in the kerosene dielectric during electro discharge machining of AISI 304. The process performance has been evaluated by means of ROC when peak current, pulse on time, gap voltage, duty cycle and powder concentration are considered as process parameters and machining is performed by using tungsten carbide electrodes (untreated and double tempered electrodes). A regression analysis was performed to correlate the data between the response and the process parameters. Microstructural analysis was carried out on the machined surfaces. Least radial overcut was observed for conventional EDM as compared to powder mixed EDM. Cryotreated double tempered electrode significantly reduced the radial overcut than untreated electrode.

Lean energy analysis of CNC lathe

NASA Astrophysics Data System (ADS)

Liana, N. A.; Amsyar, N.; Hilmy, I.; Yusof, MD

2018-01-01

The industrial sector in Malaysia is one of the main sectors that have high percentage of energy demand compared to other sector and this problem may lead to the future power shortage and increasing the production cost of a company. Suitable initiatives should be implemented by the industrial sectors to solve the issues such as by improving the machining system. In the past, the majority of the energy consumption in industry focus on lighting, HVAC and office section usage. Future trend, manufacturing process is also considered to be included in the energy analysis. A study on Lean Energy Analysis in a machining process is presented. Improving the energy efficiency in a lathe machine by enhancing the cutting parameters of turning process is discussed. Energy consumption of a lathe machine was analyzed in order to identify the effect of cutting parameters towards energy consumption. It was found that the combination of parameters for third run (spindle speed: 1065 rpm, depth of cut: 1.5 mm, feed rate: 0.3 mm/rev) was the most preferred and ideal to be used during the turning machining process as it consumed less energy usage.

Determination of the performance of vermicomposting process applied to sewage sludge by monitoring of the compost quality and immune responses in three earthworm species: Eisenia fetida, Eisenia andrei and Dendrobaena veneta.

PubMed

Suleiman, Hanine; Rorat, Agnieszka; Grobelak, Anna; Grosser, Anna; Milczarek, Marcin; Płytycz, Barbara; Kacprzak, Małgorzata; Vandenbulcke, Franck

2017-10-01

The aim of this study was to assess the effectiveness of vermicomposting process applied on three different sewage sludge (precomposted with grass clippings, sawdust and municipal solid wastes) using three different earthworm species. Selected immune parameters, namely biomarkers of stress and metal body burdens, have been used to biomonitor the vermicomposting process and to assess the impact of contaminants on earthworm's physiology. Biotic and abiotic parameters were also used in order to monitor the process and the quality of the final product. Dendrobaena veneta exhibited much lower resistance in all experimental conditions, as the bodyweight and the total number of circulating immune cells decreased in the most contaminated conditions. All earthworm species accumulated heavy metals as follows Cd>Co>Cu>Zn>Ni>Pb>Cr: Eisenia sp. worms exhibited the highest ability to accumulate several heavy metals. Vermicompost obtained after 45days was acceptable according to agronomic parameters and to compost quality norms in France and Poland. Copyright © 2017 Elsevier Ltd. All rights reserved.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Thermomechanical Simulation of the Splashing of Ceramic Droplets on a Rigid Substrate

NASA Astrophysics Data System (ADS)

Bertagnolli, Mauro; Marchese, Maurizio; Jacucci, Gianni; St. Doltsinis, Ioannis; Noelting, Swen

1997-05-01

Finite element simulation techniques have been applied to the spreading process of single ceramic liquid droplets impacting on a flat cold surface under plasma-spraying conditions. The goal of the present investigation is to predict the geometrical form of the splat as a function of technological process parameters, such as initial temperature and velocity, and to follow the thermal field developing in the droplet up to solidification. A non-linear finite element programming system has been utilized in order to model the complex physical phenomena involved in the present impact process. The Lagrangean description of the motion of the viscous melt in the drops, as constrained by surface tension and the developing contact with the target, has been coupled to an analysis of transient thermal phenomena accounting also for the solidification of the material. The present study refers to a parameter spectrum as from experimental data of technological relevance. The significance of process parameters for the most pronounced physical phenomena is discussed as are also the consequences of modelling. We consider the issue of solidification as well and touch on the effect of partially unmelted material.

Relaxation Time Distribution (RTD) of Spectral Induced Polarization (SIP) data from environmental studies

NASA Astrophysics Data System (ADS)

Ntarlagiannis, D.; Ustra, A.; Slater, L. D.; Zhang, C.; Mendonça, C. A.

2015-12-01

In this work we present an alternative formulation of the Debye Decomposition (DD) of complex conductivity spectra, with a new set of parameters that are directly related to the continuous Debye relaxation model. The procedure determines the relaxation time distribution (RTD) and two frequency-independent parameters that modulate the induced polarization spectra. The distribution of relaxation times quantifies the contribution of each distinct relaxation process, which can in turn be associated with specific polarization processes and characterized in terms of electrochemical and interfacial parameters as derived from mechanistic models. Synthetic tests show that the procedure can successfully fit spectral induced polarization (SIP) data and accurately recover the RTD. The procedure was applied to different data sets, focusing on environmental applications. We focus on data of sand-clay mixtures artificially contaminated with toluene, and crude oil-contaminated sands experiencing biodegradation. The results identify characteristic relaxation times that can be associated with distinct polarization processes resulting from either the contaminant itself or transformations associated with biodegradation. The inversion results provide information regarding the relative strength and dominant relaxation time of these polarization processes.

Optimization of Robotic Spray Painting process Parameters using Taguchi Method

NASA Astrophysics Data System (ADS)

Chidhambara, K. V.; Latha Shankar, B.; Vijaykumar

2018-02-01

Automated spray painting process is gaining interest in industry and research recently due to extensive application of spray painting in automobile industries. Automating spray painting process has advantages of improved quality, productivity, reduced labor, clean environment and particularly cost effectiveness. This study investigates the performance characteristics of an industrial robot Fanuc 250ib for an automated painting process using statistical tool Taguchi’s Design of Experiment technique. The experiment is designed using Taguchi’s L25 orthogonal array by considering three factors and five levels for each factor. The objective of this work is to explore the major control parameters and to optimize the same for the improved quality of the paint coating measured in terms of Dry Film thickness(DFT), which also results in reduced rejection. Further Analysis of Variance (ANOVA) is performed to know the influence of individual factors on DFT. It is observed that shaping air and paint flow are the most influencing parameters. Multiple regression model is formulated for estimating predicted values of DFT. Confirmation test is then conducted and comparison results show that error is within acceptable level.

The Effect of Process Parameters and Tool Geometry on Thermal Field Development and Weld Formation in Friction Stir Welding of the Alloys AZ31 and AZ61

NASA Astrophysics Data System (ADS)

Zettler, R.; Blanco, A. C.; dos Santos, J. F.; Marya, S.

An increase in the use of magnesium (Mg) in the car manufacturing industry has raised questions concerning its weldability. Friction Stir Welding (FSW) has the advantage of achieving metallic bonding below that of the melting point of the base material thus avoiding many of the metallurgical problems associated with the solidification process. The present study presents the results of a development program carried out to investigate the response of Mg alloys AZ31 and AZ61 to different FSW tool geometries and process parameters. Temperature development across the weld zone was monitored and the produced welds have been subjected to microstructural analysis and mechanical testing. Defect free welds have been produced with optimised FSW-tool and parameters. The micro structure of the welded joint resulted in similar ductility and hardness levels as compared to that of the base material. The results also demonstrated that tool geometry plays a fundamental role in the response of the investigated alloys to the FSW process.

Sensitivity analysis of the add-on price estimate for the edge-defined film-fed growth process

NASA Technical Reports Server (NTRS)

Mokashi, A. R.; Kachare, A. H.

1981-01-01

The analysis is in terms of cost parameters and production parameters. The cost parameters include equipment, space, direct labor, materials, and utilities. The production parameters include growth rate, process yield, and duty cycle. A computer program was developed specifically to do the sensitivity analysis.