Optimization of thermal protection systems for the space vehicle. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

1972-01-01

The development of the computational techniques for the design optimization of thermal protection systems for the space shuttle vehicle are discussed. The resulting computer program was then used to perform initial optimization and sensitivity studies on a typical thermal protection system (TPS) to demonstrate its application to the space shuttle TPS design. The program was developed in FORTRAN IV for CDC 6400 computer, but it was subsequently converted to the FORTRAN V language to be used on the Univac 1108.

Optimal segmentation and packaging process

DOEpatents

Kostelnik, Kevin M.; Meservey, Richard H.; Landon, Mark D.

1999-01-01

A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D&D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded.

Optimal segmentation and packaging process

DOEpatents

Kostelnik, K.M.; Meservey, R.H.; Landon, M.D.

1999-08-10

A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D and D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded. 3 figs.

Rigorous ILT optimization for advanced patterning and design-process co-optimization

NASA Astrophysics Data System (ADS)

Selinidis, Kosta; Kuechler, Bernd; Cai, Howard; Braam, Kyle; Hoppe, Wolfgang; Domnenko, Vitaly; Poonawala, Amyn; Xiao, Guangming

2018-03-01

Despite the large difficulties involved in extending 193i multiple patterning and the slow ramp of EUV lithography to full manufacturing readiness, the pace of development for new technology node variations has been accelerating. Multiple new variations of new and existing technology nodes have been introduced for a range of device applications; each variation with at least a few new process integration methods, layout constructs and/or design rules. This had led to a strong increase in the demand for predictive technology tools which can be used to quickly guide important patterning and design co-optimization decisions. In this paper, we introduce a novel hybrid predictive patterning method combining two patterning technologies which have each individually been widely used for process tuning, mask correction and process-design cooptimization. These technologies are rigorous lithography simulation and inverse lithography technology (ILT). Rigorous lithography simulation has been extensively used for process development/tuning, lithography tool user setup, photoresist hot-spot detection, photoresist-etch interaction analysis, lithography-TCAD interactions/sensitivities, source optimization and basic lithography design rule exploration. ILT has been extensively used in a range of lithographic areas including logic hot-spot fixing, memory layout correction, dense memory cell optimization, assist feature (AF) optimization, source optimization, complex patterning design rules and design-technology co-optimization (DTCO). The combined optimization capability of these two technologies will therefore have a wide range of useful applications. We investigate the benefits of the new functionality for a few of these advanced applications including correction for photoresist top loss and resist scumming hotspots.

Does optimism act as a buffer against posttraumatic stress over time? A longitudinal study of the protective role of optimism after the 2011 Oslo bombing.

PubMed

Birkeland, Marianne Skogbrott; Blix, Ines; Solberg, Øivind; Heir, Trond

2017-03-01

Cross-sectional studies have revealed that high levels of optimism can protect against high levels of posttraumatic stress after exposure to trauma. However, this is the first study to explore (a) the protective role of optimism in a longitudinal perspective and (b) optimism's protective effects on specific symptom clusters within the posttraumatic stress symptomatology. This study used prospective survey data from ministerial employees (n = 256) collected approximately 1, 2, and 3 years after the 2011 Oslo bombing. To examine relationships between optimism and development of posttraumatic stress, we applied a series of latent growth curve analyses of both overall posttraumatic stress and the 5 clusters within the posttraumatic stress symptomatology (intrusions, avoidance, numbing, dysphoric arousal, and anxious arousal) with predictors and interaction terms. The results showed that levels of exposure and optimism had main effects on starting levels of all clusters of posttraumatic stress. In addition, optimism had a protective-stabilizing effect on starting levels of avoidance, numbing, and dysphoric arousal. No associations between optimism and rate of change in symptoms clusters were found. These results suggest that optimism may help to neutralize the effects of high exposure on levels of symptoms of avoidance, numbing, and dysphoric arousal but not on the symptoms of intrusions and anxious arousal. Thus, individuals high in optimism still experience intrusions and anxious arousal after trauma, but may be better equipped to cope with these so they do not develop into avoidance, numbing and dyshorical arousal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An Optimized Integrator Windup Protection Technique Applied to a Turbofan Engine Control

NASA Technical Reports Server (NTRS)

Watts, Stephen R.; Garg, Sanjay

1995-01-01

This paper introduces a new technique for providing memoryless integrator windup protection which utilizes readily available optimization software tools. This integrator windup protection synthesis provides a concise methodology for creating integrator windup protection for each actuation system loop independently while assuring both controller and closed loop system stability. The individual actuation system loops' integrator windup protection can then be combined to provide integrator windup protection for the entire system. This technique is applied to an H(exp infinity) based multivariable control designed for a linear model of an advanced afterburning turbofan engine. The resulting transient characteristics are examined for the integrated system while encountering single and multiple actuation limits.

Marine protected areas and the value of spatially optimized fishery management

PubMed Central

Rassweiler, Andrew; Costello, Christopher; Siegel, David A.

2012-01-01

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed. PMID:22753469

Marine protected areas and the value of spatially optimized fishery management.

PubMed

Rassweiler, Andrew; Costello, Christopher; Siegel, David A

2012-07-17

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed.

Energy and Process Optimization Assessment, Fort Stewart, GA

DTIC Science & Technology

2006-04-01

ER D C/ CE R L TR -0 6 -8 Energy and Process Optimization Assessment Fort Stewart, GA John L. Vavrin, Alexander M. Zhivov, William T...distribution is unlimited. ERDC/CERL TR-06-8 April 2006 Energy and Process Optimization Assessment Fort Stewart, GA John L. Vavrin, Alexander...U.S. Army Corps of Engineers Washington, DC 20314-1000 Under Work Unit 33143 ERDC/CERL TR-06-8 ii Abstract: An Energy and Process Optimization

[Optimizing staff radiation protection in radiology by minimizing the effective dose].

PubMed

von Boetticher, H; Lachmund, J; Hoffmann, W; Luska, G

2006-03-01

In the present study the optimization of radiation protection devices is achieved by minimizing the effective dose of the staff members since the stochastic radiation effects correlate to the effective dose. Radiation exposure dosimetry was performed with TLD measurements using one Alderson Phantom in the patient position and a second phantom in the typical position of the personnel. Various types of protective clothing as well as fixed shields were considered in the calculations. It was shown that the doses of the unshielded organs (thyroid, parts of the active bone marrow) contribute significantly to the effective dose of the staff. Therefore, there is no linear relationship between the shielding factors for protective garments and the effective dose. An additional thyroid protection collar reduces the effective dose by a factor of 1.7 - 3.0. X-ray protective clothing with a 0.35 mm lead equivalent and an additional thyroid protection collar provides better protection against radiation than an apron with a 0.5 mm lead equivalent but no collar. The use of thyroid protection collars is an effective preventive measure against exceeding occupational organ dose limits, and a thyroid shield also considerably reduces the effective dose. Therefore, thyroid protection collars should be a required component of anti-X protection.

Gaussian process regression for geometry optimization

NASA Astrophysics Data System (ADS)

Denzel, Alexander; Kästner, Johannes

2018-03-01

We implemented a geometry optimizer based on Gaussian process regression (GPR) to find minimum structures on potential energy surfaces. We tested both a two times differentiable form of the Matérn kernel and the squared exponential kernel. The Matérn kernel performs much better. We give a detailed description of the optimization procedures. These include overshooting the step resulting from GPR in order to obtain a higher degree of interpolation vs. extrapolation. In a benchmark against the Limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer of the DL-FIND library on 26 test systems, we found the new optimizer to generally reduce the number of required optimization steps.

Optimization of a Tube Hydroforming Process

NASA Astrophysics Data System (ADS)

Abedrabbo, Nader; Zafar, Naeem; Averill, Ron; Pourboghrat, Farhang; Sidhu, Ranny

2004-06-01

An approach is presented to optimize a tube hydroforming process using a Genetic Algorithm (GA) search method. The goal of the study is to maximize formability by identifying the optimal internal hydraulic pressure and feed rate while satisfying the forming limit diagram (FLD). The optimization software HEEDS is used in combination with the nonlinear structural finite element code LS-DYNA to carry out the investigation. In particular, a sub-region of a circular tube blank is formed into a square die. Compared to the best results of a manual optimization procedure, a 55% increase in expansion was achieved when using the pressure and feed profiles identified by the automated optimization procedure.

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.

The role of the optimization process in illumination design

NASA Astrophysics Data System (ADS)

Gauvin, Michael A.; Jacobsen, David; Byrne, David J.

2015-07-01

This paper examines the role of the optimization process in illumination design. We will discuss why the starting point of the optimization process is crucial to a better design and why it is also important that the user understands the basic design problem and implements the correct merit function. Both a brute force method and the Downhill Simplex method will be used to demonstrate optimization methods with focus on using interactive design tools to create better starting points to streamline the optimization process.

Multiobjective optimization approach: thermal food processing.

PubMed

Abakarov, A; Sushkov, Y; Almonacid, S; Simpson, R

2009-01-01

The objective of this study was to utilize a multiobjective optimization technique for the thermal sterilization of packaged foods. The multiobjective optimization approach used in this study is based on the optimization of well-known aggregating functions by an adaptive random search algorithm. The applicability of the proposed approach was illustrated by solving widely used multiobjective test problems taken from the literature. The numerical results obtained for the multiobjective test problems and for the thermal processing problem show that the proposed approach can be effectively used for solving multiobjective optimization problems arising in the food engineering field.

A design optimization process for Space Station Freedom

NASA Technical Reports Server (NTRS)

Chamberlain, Robert G.; Fox, George; Duquette, William H.

1990-01-01

The Space Station Freedom Program is used to develop and implement a process for design optimization. Because the relative worth of arbitrary design concepts cannot be assessed directly, comparisons must be based on designs that provide the same performance from the point of view of station users; such designs can be compared in terms of life cycle cost. Since the technology required to produce a space station is widely dispersed, a decentralized optimization process is essential. A formulation of the optimization process is provided and the mathematical models designed to facilitate its implementation are described.

Optimizing skin protection with semipermeable gloves.

PubMed

Wulfhorst, Britta; Schwanitz, Hans Joachim; Bock, Meike

2004-12-01

Occlusion due to gloves is one important cause of glove irritation. Macerated softened skin gives poor protection against microbes and chemical injuries. The introduction of a breathable protective glove material would represent a significant step toward improved prevention of occupational skin disease. Performance levels of semipermeable and occlusive gloves were examined under conditions typical of the hairdressing profession. In two studies, tests comparing breathable semipermeable gloves to single-use gloves made of occlusive materials were conducted. In an initial study, a user survey was carried out in conjunction with bioengineering examinations. Values at baseline and values after gloves were worn were recorded by measuring transepidermal water loss (TEWL), skin humidity (SH), and skin surface hydrogen ion concentration (pH) in 20 healthy volunteers. In a second study, the gloves were tested for penetrability and permeability with three chemical compounds typically used in the hairdressing profession. Bioengineering examination objectively confirmed users' reports of reduced hand perspiration when semipermeable gloves were worn. The TEWL, SH, and skin surface pH values remained largely stable after 20 minutes of wearing semipermeable gloves, in contrast to the reactions observed with gloves of occlusive materials. Permeability tests indicated that the semipermeable material is effective, with some restrictions. Air leakage testing revealed that all 50 gloves tested were not airtight. Following the optimization of manufacturing methods, additional tests of the penetrability of semipermeable gloves will be necessary.

Summary of the Italian inter-society recommendations for radiation protection optimization in interventional radiology.

PubMed

Compagnone, Gaetano; Padovani, Renato; D'Avanzo, Maria Antonietta; Grande, Sveva; Campanella, Francesco; Rosi, Antonella

2018-05-01

A Working Group coordinated by the Italian National Institute of Health (Istituto Superiore di Sanità) and the National Workers Compensation Authority (Istituto Nazionale per l'Assicurazione contro gli Infortuni sul Lavoro, INAIL) and consisting of 11 Italian scientific/professional societies involved in the fluoroscopically guided interventional practices has been established to define recommendations for the optimization of patients and staff radiation protection in interventional radiology. A summary of these recommendations is here reported. A multidisciplinary approach was used to establish the Working Group by involving radiologists, interventional radiologists, neuroradiologists, interventional cardiologists, occupational health specialists, medical physicists, radiation protection experts, radiographers and nurses. The Group operated as a "Consensus Conference". Three main topics have been addressed: patient radiation protection (summarized in ten "golden rules"); staff radiation protection (summarized in ten "golden rules"); and education/training of interventional radiology professionals. In the "golden rules", practical and operational recommendations were provided to help the professionals in optimizing dose delivered to patients and reducing their own exposure. Operative indications dealt also with continuing education and training, and recommendations on professional accreditation and certification. The "Consensus Conference" was the methodology adopted for the development of these recommendations. Involvement of all professionals is a winning approach to improve practical implementation of the recommendations, thus getting a real impact on the optimization of the interventional radiology practices.

Reflector and Protections in a Sodium-cooled Fast Reactor: Modelling and Optimization

NASA Astrophysics Data System (ADS)

Blanchet, David; Fontaine, Bruno

2017-09-01

The ASTRID project (Advanced Sodium Technological Reactor for Industrial Demonstration) is a Generation IV nuclear reactor concept under development in France [1]. In this frame, studies are underway to optimize radial reflectors and protections. Considering radial protections made in natural boron carbide, this study is conducted to assess the neutronic performances of the MgO as the reference choice for reflector material, in comparison with other possible materials including a more conventional stainless steel. The analysis is based upon a simplified 1-D and 2-D deterministic modelling of the reactor, providing simplified interfaces between core, reflector and protections. Such models allow examining detailed reaction rate distributions; they also provide physical insights into local spectral effects occurring at the Core-Reflector and at the Reflector-Protection interfaces.

Process optimization by use of design of experiments: Application for liposomalization of FK506.

PubMed

Toyota, Hiroyasu; Asai, Tomohiro; Oku, Naoto

2017-05-01

Design of experiments (DoE) can accelerate the optimization of drug formulations, especially complexed formulas such as those of drugs, using delivery systems. Administration of FK506 encapsulated in liposomes (FK506 liposomes) is an effective approach to treat acute stroke in animal studies. To provide FK506 liposomes as a brain protective agent, it is necessary to manufacture these liposomes with good reproducibility. The objective of this study was to confirm the usefulness of DoE for the process-optimization study of FK506 liposomes. The Box-Behnken design was used to evaluate the effect of the process parameters on the properties of FK506 liposomes. The results of multiple regression analysis showed that there was interaction between the hydration temperature and the freeze-thaw cycle on both the particle size and encapsulation efficiency. An increase in the PBS hydration volume resulted in an increase in encapsulation efficiency. Process parameters had no effect on the ζ-potential. The multiple regression equation showed good predictability of the particle size and the encapsulation efficiency. These results indicated that manufacturing conditions must be taken into consideration to prepare liposomes with desirable properties. DoE would thus be promising approach to optimize the conditions for the manufacturing of liposomes. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of a protective medium for freeze-dried Pichia membranifaciens and application of this biocontrol agent on citrus fruit.

PubMed

Niu, X; Deng, L; Zhou, Y; Wang, W; Yao, S; Zeng, K

2016-07-01

To optimize a protective medium for freeze-dried Pichia membranifaciens and to evaluate biocontrol efficacies of agents against blue and green mould and anthracnose in citrus fruit. Based on the screening assays of saccharides and antioxidants, response surface methodology was used to optimize sucrose, sodium glutamate and skim milk to improve viability of freeze-dried Pi. membranifaciens. Biocontrol assays were conducted between fresh and freeze-dried Pi. membranifaciens against Penicillium italicum, Penicillium digitatum and Colletotrichum gloeosporioides in citrus fruit. Solving the regression equation indicated that the optimal protective medium was 6·06% (w/v) sucrose combined with 3·40% (w/v) sodium glutamate and 5·43% (w/v) skim milk. Pi. membranifaciens freeze-dried in the optimal protective medium showed 76·80% viability, and retained biocontrol efficacy against Pe. italicum, Pe. digitatum and Co. gloeosporioides in citrus fruit. The optimal protective medium showed more effective protective properties than each of the three protectants used alone. The viability of freeze-dried Pi. membranifaciens finally reached 76·80%. Meanwhile, the biocontrol efficacies showed no significant difference between fresh and freeze-dried yeast against Pe. italicum, Pe. digitatum and Co. gloeosporioides in citrus fruit. The results showed the potential value of Pi. membranifaciens CICC 32259 for commercialization. © 2016 The Society for Applied Microbiology.

Simulative design and process optimization of the two-stage stretch-blow molding process

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

Hopmann, Ch.; Rasche, S.; Windeck, C.

2015-05-22

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development timemore » and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.« less

Simulative design and process optimization of the two-stage stretch-blow molding process

NASA Astrophysics Data System (ADS)

Hopmann, Ch.; Rasche, S.; Windeck, C.

2015-05-01

The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.

Optimal design of solidification processes

NASA Technical Reports Server (NTRS)

Dantzig, Jonathan A.; Tortorelli, Daniel A.

1991-01-01

An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.

[Imaging center - optimization of the imaging process].

PubMed

Busch, H-P

2013-04-01

Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

Power Consumption Optimization in Tooth Gears Processing

NASA Astrophysics Data System (ADS)

Kanatnikov, N.; Harlamov, G.; Kanatnikova, P.; Pashmentova, A.

2018-01-01

The paper reviews the issue of optimization of technological process of tooth gears production of the power consumption criteria. The authors dwell on the indices used for cutting process estimation by the consumed energy criteria and their applicability in the analysis of the toothed wheel production process. The inventors proposed a method for optimization of power consumptions based on the spatial modeling of cutting pattern. The article is aimed at solving the problem of effective source management in order to achieve economical and ecological effect during the mechanical processing of toothed gears. The research was supported by Russian Science Foundation (project No. 17-79-10316).

Analysis and Evaluation of Parameters Determining Maximum Efficiency of Fish Protection

NASA Astrophysics Data System (ADS)

Khetsuriani, E. D.; Kostyukov, V. P.; Khetsuriani, T. E.

2017-11-01

The article is concerned with experimental research findings. The efficiency of fish fry protection from entering water inlets is the main criterion of any fish protection facility or device. The research was aimed to determine an adequate mathematical model E = f(PCT, Vp, α), where PCT, Vp and α are controlled factors influencing the process of fish fry protection. The result of the processing of experimental data was an adequate regression model. We determined the maximum of fish protection Emax=94,21 and the minimum of optimization function Emin=44,41. As a result of the statistical processing of experimental data we obtained adequate dependences for determining an optimal rotational speed of tip and fish protection efficiency. The analysis of fish protection efficiency dependence E% = f(PCT, Vp, α) allowed the authors to recommend the following optimized operating modes for it: the maximum fish protection efficiency is achieved at the process pressure PCT=3 atm, stream velocity Vp=0,42 m/s and nozzle inclination angle α=47°49’. The stream velocity Vp has the most critical influence on fish protection efficiency. The maximum efficiency of fish protection is obtained at the tip rotational speed of 70.92 rpm.

Optimization of a reversible hood for protecting a pedestrian's head during car collisions.

PubMed

Huang, Sunan; Yang, Jikuang

2010-07-01

This study evaluated and optimized the performance of a reversible hood (RH) for the prevention of the head injuries of an adult pedestrian from car collisions. The FE model of a production car front was introduced and validated. The baseline RH was developed from the original hood in the validated car front model. In order to evaluate the protective performance of the baseline RH, the FE models of an adult headform and a 50th percentile human head were used in parallel to impact the baseline RH. Based on the evaluation, the response surface method was applied to optimize the RH in terms of the material stiffness, lifting speed, and lifted height. Finally, the headform model and the human head model were again used to evaluate the protective performance of the optimized RH. It was found that the lifted baseline RH can obviously reduce the impact responses of the headform model and the human head model by comparing with the retracted and lifting baseline RH. When the optimized RH was lifted, the HIC values of the headform model and the human head model were further reduced to much lower than 1000. The risk of pedestrian head injuries can be prevented as required by EEVC WG17. Copyright 2009 Elsevier Ltd. All rights reserved.

A Taguchi approach on optimal process control parameters for HDPE pipe extrusion process

NASA Astrophysics Data System (ADS)

Sharma, G. V. S. S.; Rao, R. Umamaheswara; Rao, P. Srinivasa

2017-06-01

High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio ( S/ N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166 °C, Dimmer speed at 08 rpm, and Die head temperature to be 192 °C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of

Automated electrochemical assembly of the protected potential TMG-chitotriomycin precursor based on rational optimization of the carbohydrate building block.

PubMed

Nokami, Toshiki; Isoda, Yuta; Sasaki, Norihiko; Takaiso, Aki; Hayase, Shuichi; Itoh, Toshiyuki; Hayashi, Ryutaro; Shimizu, Akihiro; Yoshida, Jun-ichi

2015-03-20

The anomeric arylthio group and the hydroxyl-protecting groups of thioglycosides were optimized to construct carbohydrate building blocks for automated electrochemical solution-phase synthesis of oligoglucosamines having 1,4-β-glycosidic linkages. The optimization study included density functional theory calculations, measurements of the oxidation potentials, and the trial synthesis of the chitotriose trisaccharide. The automated synthesis of the protected potential N,N,N-trimethyl-d-glucosaminylchitotriomycin precursor was accomplished by using the optimized building block.

Optimal design of upstream processes in biotransformation technologies.

PubMed

Dheskali, Endrit; Michailidi, Katerina; de Castro, Aline Machado; Koutinas, Apostolis A; Kookos, Ioannis K

2017-01-01

In this work a mathematical programming model for the optimal design of the bioreaction section of biotechnological processes is presented. Equations for the estimation of the equipment cost derived from a recent publication by the US National Renewable Energy Laboratory (NREL) are also summarized. The cost-optimal design of process units and the optimal scheduling of their operation can be obtained using the proposed formulation that has been implemented in software available from the journal web page or the corresponding author. The proposed optimization model can be used to quantify the effects of decisions taken at a lab scale on the industrial scale process economics. It is of paramount important to note that this can be achieved at the early stage of the development of a biotechnological project. Two case studies are presented that demonstrate the usefulness and potential of the proposed methodology. Copyright © 2016. Published by Elsevier Ltd.

[Hygienic optimization of the use of chemical protective means on railway transport].

PubMed

Kaptsov, V A; Pankova, V B; Elizarov, B B; Mezentsev, A P; Komleva, E A

2004-01-01

The paper presents data characterizing the working conditions of railway workers. It shows that there is the greatest levels of noise and vibration, the burden and intensity of work. The worst working conditions are noted in energy supply, car, locomotive services and track facilities. The working conditions determine a significant industrial risk of railway workers since the prevention of health abnormalities by using chemical protective means is a topical problem. The priority lines of hygienic rationale for optimization the choice and use of chemical protective means for workers exposed to occupational hazards are determined.

Optimization of thermal processing of canned mussels.

PubMed

Ansorena, M R; Salvadori, V O

2011-10-01

The design and optimization of thermal processing of solid-liquid food mixtures, such as canned mussels, requires the knowledge of the thermal history at the slowest heating point. In general, this point does not coincide with the geometrical center of the can, and the results show that it is located along the axial axis at a height that depends on the brine content. In this study, a mathematical model for the prediction of the temperature at this point was developed using the discrete transfer function approach. Transfer function coefficients were experimentally obtained, and prediction equations fitted to consider other can dimensions and sampling interval. This model was coupled with an optimization routine in order to search for different retort temperature profiles to maximize a quality index. Both constant retort temperature (CRT) and variable retort temperature (VRT; discrete step-wise and exponential) were considered. In the CRT process, the optimal retort temperature was always between 134 °C and 137 °C, and high values of thiamine retention were achieved. A significant improvement in surface quality index was obtained for optimal VRT profiles compared to optimal CRT. The optimization procedure shown in this study produces results that justify its utilization in the industry.

Process and Energy Optimization Assessment, Rock Island Arsenal, IL

DTIC Science & Technology

2004-09-01

Approved for public release; distribution is unlimited. ER D C /C ER L TR -0 4- 17 Process and Energy Optimization Assessment Rock Island... Optimization Assessment: Rock Island Arsenal, IL Mike C.J. Lin, Alexander M. Zhivov, and Veera M. Boddu, Construction Engineering Research...and Energy Optimization Assessment (PEOA) was conducted at Rock Island Arsenal (RIA), IL to identify process, energy, and environmental opportunities

Bidirectional optimization of the melting spinning process.

PubMed

Liang, Xiao; Ding, Yongsheng; Wang, Zidong; Hao, Kuangrong; Hone, Kate; Wang, Huaping

2014-02-01

A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.

Multicast Routing and Wavelength Assignment with Shared Protection in Multi-Fiber WDM Mesh Networks: Optimal and Heuristic Solutions

NASA Astrophysics Data System (ADS)

Woradit, Kampol; Guyot, Matthieu; Vanichchanunt, Pisit; Saengudomlert, Poompat; Wuttisittikulkij, Lunchakorn

While the problem of multicast routing and wavelength assignment (MC-RWA) in optical wavelength division multiplexing (WDM) networks has been investigated, relatively few researchers have considered network survivability for multicasting. This paper provides an optimization framework to solve the MC-RWA problem in a multi-fiber WDM network that can recover from a single-link failure with shared protection. Using the light-tree (LT) concept to support multicast sessions, we consider two protection strategies that try to reduce service disruptions after a link failure. The first strategy, called light-tree reconfiguration (LTR) protection, computes a new multicast LT for each session affected by the failure. The second strategy, called optical branch reconfiguration (OBR) protection, tries to restore a logical connection between two adjacent multicast members disconnected by the failure. To solve the MC-RWA problem optimally, we propose an integer linear programming (ILP) formulation that minimizes the total number of fibers required for both working and backup traffic. The ILP formulation takes into account joint routing of working and backup traffic, the wavelength continuity constraint, and the limited splitting degree of multicast-capable optical cross-connects (MC-OXCs). After showing some numerical results for optimal solutions, we propose heuristic algorithms that reduce the computational complexity and make the problem solvable for large networks. Numerical results suggest that the proposed heuristic yields efficient solutions compared to optimal solutions obtained from exact optimization.

Instrumentation for optimizing an underground coal-gasification process

NASA Astrophysics Data System (ADS)

Seabaugh, W.; Zielinski, R. E.

1982-06-01

While the United States has a coal resource base of 6.4 trillion tons, only seven percent is presently recoverable by mining. The process of in-situ gasification can recover another twenty-eight percent of the vast resource, however, viable technology must be developed for effective in-situ recovery. The key to this technology is system that can optimize and control the process in real-time. An instrumentation system is described that optimizes the composition of the injection gas, controls the in-situ process and conditions the product gas for maximum utilization. The key elements of this system are Monsanto PRISM Systems, a real-time analytical system, and a real-time data acquisition and control system. This system provides from complete automation of the process but can easily be overridden by manual control. The use of this cost effective system can provide process optimization and is an effective element in developing a viable in-situ technology.

Intelligent Processing Equipment Within the Environmental Protection Agency

NASA Technical Reports Server (NTRS)

Greathouse, Daniel G.; Nalesnik, Richard P.

1992-01-01

Protection of the environment and environmental remediation requires the cooperation, at all levels, of government and industry. Intelligent processing equipment, in addition to other artificial intelligence based tools, was used by the Environmental Protection Agency to provide personnel safety and improve the efficiency of those responsible for protection and remediation of the environment. These exploratory efforts demonstrate the feasibility and utility of expanding development and widespread use of these tools. A survey of current intelligent processing equipment applications in the Agency is presented and is followed by a brief discussion of possible uses in the future.

Plasma sprayed manganese-cobalt spinel coatings: Process sensitivity on phase, electrical and protective performance

NASA Astrophysics Data System (ADS)

Han, Su Jung; Pala, Zdenek; Sampath, Sanjay

2016-02-01

Manganese cobalt spinel (Mn1.5Co1.5O4, MCO) coatings are prepared by the air plasma spray (APS) process to examine their efficacy in serving as protective coatings from Cr-poisoning of the cathode side in intermediate temperature-solid oxide fuel cells (IT-SOFCs). These complex oxides are susceptible to process induced stoichiometric and phase changes which affect their functional performance. To critically examine these effects, MCO coatings are produced with deliberate modifications to the spray process parameters to explore relationship among process conditions, microstructure and functional properties. The resultant interplay among particle thermal and kinetic energies are captured through process maps, which serve to characterize the parametric effects on properties. The results show significant changes to the chemistry and phase composition of the deposited material resulting from preferential evaporation of oxygen. Post deposition annealing recovers oxygen in the coatings and allows partial recovery of the spinel phase, which is confirmed through thermo-gravimetric analysis (TGA)/differential scanning calorimetry (DSC), X-ray Diffraction (XRD), and magnetic hysteresis measurements. In addition, coatings with high density after sintering show excellent electrical conductivity of 40 S cm-1 at 800 °C while simultaneously providing requisite protection characteristics against Cr-poisoning. This study provides a framework for optimal evaluation of MCO coatings in intermediate temperature SOFCs.

INTELLIGENT PROCESSING EQUIPMENT WITHIN THE ENVIRONMENTAL PROTECTION AGENCY

EPA Science Inventory

Protection of the environment and environmental remediation requires the cooperation -at all levels- of government and industry. ntelligent processing equipment, in addition to other artificial intelligence based tools, has been used by the Environmental Protection Agency to prov...

Optimizing a Laser Process for Making Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Arepalli, Sivaram; Nikolaev, Pavel; Holmes, William

2010-01-01

A systematic experimental study has been performed to determine the effects of each of the operating conditions in a double-pulse laser ablation process that is used to produce single-wall carbon nanotubes (SWCNTs). The comprehensive data compiled in this study have been analyzed to recommend conditions for optimizing the process and scaling up the process for mass production. The double-pulse laser ablation process for making SWCNTs was developed by Rice University researchers. Of all currently known nanotube-synthesizing processes (arc and chemical vapor deposition), this process yields the greatest proportion of SWCNTs in the product material. The aforementioned process conditions are important for optimizing the production of SWCNTs and scaling up production. Reports of previous research (mostly at Rice University) toward optimization of process conditions mention effects of oven temperature and briefly mention effects of flow conditions, but no systematic, comprehensive study of the effects of process conditions was done prior to the study described here. This was a parametric study, in which several production runs were carried out, changing one operating condition for each run. The study involved variation of a total of nine parameters: the sequence of the laser pulses, pulse-separation time, laser pulse energy density, buffer gas (helium or nitrogen instead of argon), oven temperature, pressure, flow speed, inner diameter of the flow tube, and flow-tube material.

Risk and Resilience in Pediatric Chronic Pain: Exploring the Protective Role of Optimism.

PubMed

Cousins, Laura A; Cohen, Lindsey L; Venable, Claudia

2015-10-01

Fear of pain and pain catastrophizing are prominent risk factors for pediatric chronic pain-related maladjustment. Although resilience has largely been ignored in the pediatric pain literature, prior research suggests that optimism might benefit youth and can be learned. We applied an adult chronic pain risk-resilience model to examine the interplay of risk factors and optimism on functioning outcomes in youth with chronic pain. Participants included 58 children and adolescents (8-17 years) attending a chronic pain clinic and their parents. Participants completed measures of fear of pain, pain catastrophizing, optimism, disability, and quality of life. Consistent with the literature, pain intensity, fear of pain, and catastrophizing predicted functioning. Optimism was a unique predictor of quality of life, and optimism contributed to better functioning by minimizing pain-related fear and catastrophizing. Optimism might be protective and offset the negative influence of fear of pain and catastrophizing on pain-related functioning. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An atmosphere protection subsystem in the thermal power station automated process control system

NASA Astrophysics Data System (ADS)

Parchevskii, V. M.; Kislov, E. A.

2014-03-01

Matters concerned with development of methodical and mathematical support for an atmosphere protection subsystem in the thermal power station automated process control system are considered taking as an example the problem of controlling nitrogen oxide emissions at a gas-and-oil-fired thermal power station. The combined environmental-and-economic characteristics of boilers, which correlate the costs for suppressing emissions with the boiler steam load and mass discharge of nitrogen oxides in analytic form, are used as the main tool for optimal control. A procedure for constructing and applying environmental-and-economic characteristics on the basis of technical facilities available in modern instrumentation and control systems is presented.

On process optimization considering LCA methodology.

PubMed

Pieragostini, Carla; Mussati, Miguel C; Aguirre, Pío

2012-04-15

The goal of this work is to research the state-of-the-art in process optimization techniques and tools based on LCA, focused in the process engineering field. A collection of methods, approaches, applications, specific software packages, and insights regarding experiences and progress made in applying the LCA methodology coupled to optimization frameworks is provided, and general trends are identified. The "cradle-to-gate" concept to define the system boundaries is the most used approach in practice, instead of the "cradle-to-grave" approach. Normally, the relationship between inventory data and impact category indicators is linearly expressed by the characterization factors; then, synergic effects of the contaminants are neglected. Among the LCIA methods, the eco-indicator 99, which is based on the endpoint category and the panel method, is the most used in practice. A single environmental impact function, resulting from the aggregation of environmental impacts, is formulated as the environmental objective in most analyzed cases. SimaPro is the most used software for LCA applications in literature analyzed. The multi-objective optimization is the most used approach for dealing with this kind of problems, where the ε-constraint method for generating the Pareto set is the most applied technique. However, a renewed interest in formulating a single economic objective function in optimization frameworks can be observed, favored by the development of life cycle cost software and progress made in assessing costs of environmental externalities. Finally, a trend to deal with multi-period scenarios into integrated LCA-optimization frameworks can be distinguished providing more accurate results upon data availability. Copyright © 2011 Elsevier Ltd. All rights reserved.

Design and Optimization of an Austenitic TRIP Steel for Blast and Fragment Protection

NASA Astrophysics Data System (ADS)

Feinberg, Zechariah Daniel

In light of the pervasive nature of terrorist attacks, there is a pressing need for the design and optimization of next generation materials for blast and fragment protection applications. Sadhukhan used computational tools and a systems-based approach to design TRIP-120---a fully austenitic transformation-induced plasticity (TRIP) steel. Current work more completely evaluates the mechanical properties of the prototype, optimizes the processing for high performance in tension and shear, and builds models for more predictive power of the mechanical behavior and austenite stability. Under quasi-static and dynamic tension and shear, the design exhibits high strength and high uniform ductility as a result of a strain hardening effect that arises with martensitic transformation. Significantly more martensitic transformation occurred under quasi-static loading conditions (69% in tension and 52% in shear) compared to dynamic loading conditions (13% tension and 5% in shear). Nonetheless, significant transformation occurs at high-strain rates which increases strain hardening, delays the onset of necking instability, and increases total energy absorption under adiabatic conditions. Although TRIP-120 effectively utilizes a TRIP effect to delay necking instability, a common trend of abrupt failure with limited fracture ductility was observed in tension and shear at all strain rates. Further characterization of the structure of TRIP-120 showed that an undesired grain boundary cellular reaction (η phase formation) consumed the fine dispersion of the metastable gamma' phase and limited the fracture ductility. A warm working procedure was added to the processing of TRIP-120 in order to eliminate the grain boundary cellular reaction from the structure. By eliminating η formation at the grain boundaries, warm-worked TRIP-120 exhibits a drastic improvement in the mechanical properties in tension and shear. In quasi-static tension, the optimized warm-worked TRIP-120 with an Mssigma

Design and Analysis of Optimization Algorithms to Minimize Cryptographic Processing in BGP Security Protocols.

PubMed

Sriram, Vinay K; Montgomery, Doug

2017-07-01

The Internet is subject to attacks due to vulnerabilities in its routing protocols. One proposed approach to attain greater security is to cryptographically protect network reachability announcements exchanged between Border Gateway Protocol (BGP) routers. This study proposes and evaluates the performance and efficiency of various optimization algorithms for validation of digitally signed BGP updates. In particular, this investigation focuses on the BGPSEC (BGP with SECurity extensions) protocol, currently under consideration for standardization in the Internet Engineering Task Force. We analyze three basic BGPSEC update processing algorithms: Unoptimized, Cache Common Segments (CCS) optimization, and Best Path Only (BPO) optimization. We further propose and study cache management schemes to be used in conjunction with the CCS and BPO algorithms. The performance metrics used in the analyses are: (1) routing table convergence time after BGPSEC peering reset or router reboot events and (2) peak-second signature verification workload. Both analytical modeling and detailed trace-driven simulation were performed. Results show that the BPO algorithm is 330% to 628% faster than the unoptimized algorithm for routing table convergence in a typical Internet core-facing provider edge router.

Cooperative optimization of reconfigurable machine tool configurations and production process plan

NASA Astrophysics Data System (ADS)

Xie, Nan; Li, Aiping; Xue, Wei

2012-09-01

The production process plan design and configurations of reconfigurable machine tool (RMT) interact with each other. Reasonable process plans with suitable configurations of RMT help to improve product quality and reduce production cost. Therefore, a cooperative strategy is needed to concurrently solve the above issue. In this paper, the cooperative optimization model for RMT configurations and production process plan is presented. Its objectives take into account both impacts of process and configuration. Moreover, a novel genetic algorithm is also developed to provide optimal or near-optimal solutions: firstly, its chromosome is redesigned which is composed of three parts, operations, process plan and configurations of RMTs, respectively; secondly, its new selection, crossover and mutation operators are also developed to deal with the process constraints from operation processes (OP) graph, otherwise these operators could generate illegal solutions violating the limits; eventually the optimal configurations for RMT under optimal process plan design can be obtained. At last, a manufacturing line case is applied which is composed of three RMTs. It is shown from the case that the optimal process plan and configurations of RMT are concurrently obtained, and the production cost decreases 6.28% and nonmonetary performance increases 22%. The proposed method can figure out both RMT configurations and production process, improve production capacity, functions and equipment utilization for RMT.

Information processing capacity while wearing personal protective eyewear.

PubMed

Wade, Chip; Davis, Jerry; Marzilli, Thomas S; Weimar, Wendi H

2006-08-15

It is difficult to overemphasize the function vision plays in information processing, specifically in maintaining postural control. Vision appears to be an immediate, effortless event; suggesting that eyes need only to be open to employ the visual information provided by the environment. This study is focused on investigating the effect of Occupational Safety and Health Administration regulated personal protective eyewear (29 CFR 1910.133) on physiological and cognitive factors associated with information processing capabilities. Twenty-one college students between the ages of 19 and 25 years were randomly tested in each of three eyewear conditions (control, new and artificially aged) on an inclined and horizontal support surface for auditory and visual stimulus reaction time. Data collection trials consisted of 50 randomly selected (25 auditory, 25 visual) stimuli over a 10-min surface-eyewear condition trial. Auditory stimulus reaction time was significantly affected by the surface by eyewear interaction (F2,40 = 7.4; p < 0.05). Similarly, analysis revealed a significant surface by eyewear interaction in reaction time following the visual stimulus (F2,40 = 21.7; p < 0.05). The current findings do not trivialize the importance of personal protective eyewear usage in an occupational setting; rather, they suggest the value of future research focused on the effect that personal protective eyewear has on the physiological, cognitive and biomechanical contributions to postural control. These findings suggest that while personal protective eyewear may serve to protect an individual from eye injury, an individual's use of such personal protective eyewear may have deleterious effects on sensory information associated with information processing and postural control.

Quality of mango nectar processed by high-pressure homogenization with optimized heat treatment.

PubMed

Tribst, Alline Artigiani Lima; Franchi, Mark Alexandrow; de Massaguer, Pilar Rodriguez; Cristianini, Marcelo

2011-03-01

This work aimed to evaluate the effect of high-pressure homogenization (HPH) with heat shock on Aspergillus niger, vitamin C, and color of mango nectar. The nectar was processed at 200 MPa followed by heat shock, which was optimized by response surface methodology by using mango nectar ratio (45 to 70), heat time (10 to 20), and temperature (60 to 85 °C) as variables. The color of mango nectar and vitamin C retention were evaluated at the optimized treatments, that is, 200 MPa + 61.5 °C/20 min or 73.5 °C/10 min. The mathematical model indicates that heat shock time and temperature showed a positive effect in the mould inactivation, whereas increasing ratio resulted in a protective effect on A. niger. The optimized treatments did not increase the retention of vitamin C, but had positive effect for the nectar color, in particular for samples treated at 200 MPa + 61.5 °C/20 min. The results obtained in this study show that the conidia can be inactivated by applying HPH with heat shock, particularly to apply HPH as an option to pasteurize fruit nectar for industries.

Pavement maintenance optimization model using Markov Decision Processes

NASA Astrophysics Data System (ADS)

Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

2017-09-01

This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

Utilization of Supercapacitors in Adaptive Protection Applications for Resiliency against Communication Failures: A Size and Cost Optimization Case Study

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

Habib, Hany F; El Hariri, Mohamad; Elsayed, Ahmed

Microgrids’ adaptive protection techniques rely on communication signals from the point of common coupling to ad- just the corresponding relays’ settings for either grid-connected or islanded modes of operation. However, during communication out- ages or in the event of a cyberattack, relays settings are not changed. Thus adaptive protection schemes are rendered unsuc- cessful. Due to their fast response, supercapacitors, which are pre- sent in the microgrid to feed pulse loads, could also be utilized to enhance the resiliency of adaptive protection schemes to communi- cation outages. Proper sizing of the supercapacitors is therefore im- portant in order to maintainmore » a stable system operation and also reg- ulate the protection scheme’s cost. This paper presents a two-level optimization scheme for minimizing the supercapacitor size along with optimizing its controllers’ parameters. The latter will lead to a reduction of the supercapacitor fault current contribution and an increase in that of other AC resources in the microgrid in the ex- treme case of having a fault occurring simultaneously with a pulse load. It was also shown that the size of the supercapacitor can be reduced if the pulse load is temporary disconnected during the transient fault period. Simulations showed that the resulting super- capacitor size and the optimized controller parameters from the proposed two-level optimization scheme were feeding enough fault currents for different types of faults and minimizing the cost of the protection scheme.« less

Optimization of airport security process

NASA Astrophysics Data System (ADS)

Wei, Jianan

2017-05-01

In order to facilitate passenger travel, on the basis of ensuring public safety, the airport security process and scheduling to optimize. The stochastic Petri net is used to simulate the single channel security process, draw the reachable graph, construct the homogeneous Markov chain to realize the performance analysis of the security process network, and find the bottleneck to limit the passenger throughput. Curve changes in the flow of passengers to open a security channel for the initial state. When the passenger arrives at a rate that exceeds the processing capacity of the security channel, it is queued. The passenger reaches the acceptable threshold of the queuing time as the time to open or close the next channel, simulate the number of dynamic security channel scheduling to reduce the passenger queuing time.

On the optimization of endoreversible processes

NASA Astrophysics Data System (ADS)

Pescetti, D.

2014-03-01

This paper is intended for undergraduates and specialists in thermodynamics and related areas. We consider and discuss the optimization of endoreversible thermodynamic processes under the condition of maximum work production. Explicit thermodynamic analyses of the solutions are carried out for the Novikov and Agrawal processes. It is shown that the efficiencies at maximum work production and maximum power output are not necessarily equal. They are for the Novikov process but not for the Agrawal process. The role of the constraints is put into evidence. The physical aspects are enhanced by the simplicity of the involved mathematics.

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.

Process Optimization Assessment: Fort Leonard Wood, MO and Fort Carson, CO

DTIC Science & Technology

2003-11-01

IUJ US Army Corps of Engineers, Engineer Research and Development Center Process Optimization Assessment Fort Leonard Wood, MO and Fort Carson, CO... Optimization Assessment: Fort Leonard Wood, MO and Fort Carson, CO Mike C.J. Lin and John Vavrin Construction Engineering Research Laboratory PO Box 9005...work performed a Process Optimization Assessment (POA) on behalf of Fort Leonard Wood, MO and Fort Carson, CO to identify process, energy, and

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.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

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.

Application of simulation models for the optimization of business processes

NASA Astrophysics Data System (ADS)

Jašek, Roman; Sedláček, Michal; Chramcov, Bronislav; Dvořák, Jiří

2016-06-01

The paper deals with the applications of modeling and simulation tools in the optimization of business processes, especially in solving an optimization of signal flow in security company. As a modeling tool was selected Simul8 software that is used to process modeling based on discrete event simulation and which enables the creation of a visual model of production and distribution processes.

Design Time Optimization for Hardware Watermarking Protection of HDL Designs

PubMed Central

Castillo, E.; Morales, D. P.; García, A.; Parrilla, L.; Todorovich, E.; Meyer-Baese, U.

2015-01-01

HDL-level design offers important advantages for the application of watermarking to IP cores, but its complexity also requires tools automating these watermarking algorithms. A new tool for signature distribution through combinational logic is proposed in this work. IPP@HDL, a previously proposed high-level watermarking technique, has been employed for evaluating the tool. IPP@HDL relies on spreading the bits of a digital signature at the HDL design level using combinational logic included within the original system. The development of this new tool for the signature distribution has not only extended and eased the applicability of this IPP technique, but it has also improved the signature hosting process itself. Three algorithms were studied in order to develop this automated tool. The selection of a cost function determines the best hosting solutions in terms of area and performance penalties on the IP core to protect. An 1D-DWT core and MD5 and SHA1 digital signatures were used in order to illustrate the benefits of the new tool and its optimization related to the extraction logic resources. Among the proposed algorithms, the alternative based on simulated annealing reduces the additional resources while maintaining an acceptable computation time and also saving designer effort and time. PMID:25861681

Optimal fabrication processes for unidirectional metal-matrix composites: A computational simulation

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Murthy, P. L. N.; Morel, M.

1990-01-01

A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with non-linear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.

Optimal fabrication processes for unidirectional metal-matrix composites - A computational simulation

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Murthy, P. L. N.; Morel, M.

1990-01-01

A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with nonlinear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.

Integration of Product, Package, Process, and Environment: A Food System Optimization

NASA Technical Reports Server (NTRS)

Cooper, Maya R.; Douglas, Grace L.

2015-01-01

temperature and pressure were linked to final product quality in freeze-dried corn, indicating processing modifications that could lead to improved product shelf life. Storage temperatures and packaging systems were also assessed for the impact to food quality. Reduced temperature storage had inconclusive impact to the progression of rancidity in butter cookies. Frozen storage was detrimental to fruit and vegetable textural attributes but refrigerated storage helped to sustain color and organoleptic ratings for plant-based foods. With regard to packaging systems, the metallized film overwrap significantly decreased the progression of the rancidity of butter cookies as compared to the highest barrier non-metallized film. The inclusion of oxygen scavengers resulted in noticeable moisture gains in butter cookies over time, independent of packaging film systems. Neither emergent processing technology nor the freeze dry optimization resulted in compelling quality differences from current space food provisions such that a five-year shelf life is likely with these processing changes alone. Using a combination of refrigeration and PATS processing is expected to result in organoleptically-acceptable fruit quality for most fruits through five years. The vitamin degradation will be aided somewhat by the cold temperatures but, given the labile nature of vitamin C, a more stable fortification method, such as encapsulation, should also be investigated to ensure vitamin delivery throughout the product life. Similarly, significant improvement to the packaging film used in the MATS processing, optimization of formulation for dielectric properties, vitamin fortification, and reduced temperature storage should be investigated as a hurdle approach to reach a five year shelf life in wet-pack entrees and soups. Baked goods and other environmentally-sensitive spaceflight foods will require an almost impenetrable barrier to protect the foods from oxygen and moisture ingress but scavengers and

Maximizing the efficiency of multienzyme process by stoichiometry optimization.

PubMed

Dvorak, Pavel; Kurumbang, Nagendra P; Bendl, Jaroslav; Brezovsky, Jan; Prokop, Zbynek; Damborsky, Jiri

2014-09-05

Multienzyme processes represent an important area of biocatalysis. Their efficiency can be enhanced by optimization of the stoichiometry of the biocatalysts. Here we present a workflow for maximizing the efficiency of a three-enzyme system catalyzing a five-step chemical conversion. Kinetic models of pathways with wild-type or engineered enzymes were built, and the enzyme stoichiometry of each pathway was optimized. Mathematical modeling and one-pot multienzyme experiments provided detailed insights into pathway dynamics, enabled the selection of a suitable engineered enzyme, and afforded high efficiency while minimizing biocatalyst loadings. Optimizing the stoichiometry in a pathway with an engineered enzyme reduced the total biocatalyst load by an impressive 56 %. Our new workflow represents a broadly applicable strategy for optimizing multienzyme processes. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal conditions of LDR to protect the kidney from diabetes

PubMed Central

Cheng, Jie; Li, Fengsheng; Cui, Jiuwei; Guo, Weiying; Li, Cai; Li, Wei; Wang, Guixia; Xing, Xiao; Gao, Ying; Ge, Yuanyuan; Wang, Guanjun; Cai, Lu

2014-01-01

Aims We reported the attenuation of diabetes-induced renal dysfunction by exposure to multiple low-dose radiation (LDR) at 25 mGy every other day via suppressing renal oxidative damage. We here explored the optimal conditions of LDR to protect the kidney from diabetes. Main methods Type 1 diabetic mice were induced with multiple injections of low-dose streptozotocin in male C57BL/6J mice. Diabetic mice received whole body X-irradiation at dose of 12.5, 25 or 50 mGy every other day for either 4 or 8 weeks. Age-matched normal mice were similarly irradiated at the dose of 25 mGy for 4 or 8 weeks. The renal function and histopathological changes were examined at the 4th and 8th week of the study. Key findings Diabetes induced renal dysfunction, shown by the decreased creatinine and increased microalbumin in urinary. Renal oxidative damage, detected by protein nitration and lipid oxidation, and remodeling, reflected by increased expression of connective tissue growth factor, collagen IV and fibronectin, were significantly increased in diabetic mice. All these renal pathological and function changes in diabetic mice were significantly attenuated by exposure to LDR at all regimens, among which, however, exposure to LDR at 12.5 mGy for 8 weeks provided the best preventive effect on the kidney of diabetic mice. Significance Our results suggest that whole-body LDR at 12.5 mGy every other day for 8 weeks is the optimal condition of LDR to protect the kidney from diabetes. PMID:24631139

Suborbital spaceplane optimization using non-stationary Gaussian processes

NASA Astrophysics Data System (ADS)

Dufour, Robin; de Muelenaere, Julien; Elham, Ali

2014-10-01

This paper presents multidisciplinary design optimization of a sub-orbital spaceplane. The optimization includes three disciplines: the aerodynamics, the structure and the trajectory. An Adjoint Euler code is used to calculate the aerodynamic lift and drag of the vehicle as well as their derivatives with respect to the design variables. A new surrogate model has been developed based on a non-stationary Gaussian process. That model was used to estimate the aerodynamic characteristics of the vehicle during the trajectory optimization. The trajectory of thevehicle has been optimized together with its geometry in order to maximize the amount of payload that can be carried by the spaceplane.

Optimization and standardization of pavement management processes.

DOT National Transportation Integrated Search

2004-08-01

This report addresses issues related to optimization and standardization of current pavement management processes in Kentucky. Historical pavement management records were analyzed, which indicates that standardization is necessary in future pavement ...

Comprehensive optimization process of paranasal sinus radiography.

PubMed

Saarakkala, S; Nironen, K; Hermunen, H; Aarnio, J; Heikkinen, J O

2009-04-01

The optimization of radiological examinations is important in order to reduce unnecessary patient radiation exposure. To perform a comprehensive optimization process for paranasal sinus radiography at Mikkeli Central Hospital, Finland. Patients with suspicion of acute sinusitis were imaged with a Kodak computed radiography (CR) system (n=20) and with a Philips digital radiography (DR) system (n=30) using focus-detector distances (FDDs) of 110 cm, 150 cm, or 200 cm. Patients' radiation exposure was determined in terms of entrance surface dose and dose-area product. Furthermore, an anatomical phantom was used for the estimation of point doses inside the head. Clinical image quality was evaluated by an experienced radiologist, and physical image quality was evaluated from the digital radiography phantom. Patient doses were significantly lower and image quality better with the DR system compared to the CR system. The differences in patient dose and physical image quality were small with varying FDD. Clinical image quality of the DR system was lowest with FDD of 200 cm. Further, imaging with FDD of 150 cm was technically easier for the technologist to perform than with FDD of 110 cm. After optimization, it was recommended that the DR system with FDD of 150 cm should always be used at Mikkeli Central Hospital. We recommend this kind of comprehensive approach in all optimization processes of radiological examinations.

Data processing and optimization system to study prospective interstate power interconnections

NASA Astrophysics Data System (ADS)

Podkovalnikov, Sergei; Trofimov, Ivan; Trofimov, Leonid

2018-01-01

The paper presents Data processing and optimization system for studying and making rational decisions on the formation of interstate electric power interconnections, with aim to increasing effectiveness of their functioning and expansion. The technologies for building and integrating a Data processing and optimization system including an object-oriented database and a predictive mathematical model for optimizing the expansion of electric power systems ORIRES, are described. The technology of collection and pre-processing of non-structured data collected from various sources and its loading to the object-oriented database, as well as processing and presentation of information in the GIS system are described. One of the approaches of graphical visualization of the results of optimization model is considered on the example of calculating the option for expansion of the South Korean electric power grid.

Plasma Spray and Pack Cementation Process Optimization and Oxidation Behaviour of Novel Multilayered Coatings

NASA Astrophysics Data System (ADS)

Gao, Feng

The hot section components in gas turbines are subjected to a harsh environment with the temperature being increased continuously. The higher temperature has directly resulted in severe oxidation of these components. Monolithic coatings such as MCrAIY and aluminide have been traditionally used to protect the components from oxidation; however, increased operating temperature quickly deteriorates the coatings due to accelerated diffusion of aluminum in the coatings. To improve the oxidation resistance a group of multilayered coatings are developed in this study. The multilayered coatings consist of a Cr-Si co-deposited layer as the diffusion barrier, a plasma sprayed NiCrA1Y coating as the middle layer and an aluminized top layer. The Cr-Si and aluminized layers are fabricated using pack cementation processes and the NiCrA1Y coatings are produced using the Mettech Axial III(TM) System. All of the coating processes are optimized using the methodology of Design of Experiments (DOE) and the results are analyzed using statistical method. The optimal processes are adopted to fabricate the multilayered coatings for oxidation tests. The coatings are exposed in air at 1050°C and 1150°C for 1000 hr. The results indicate that a Cr layer and a silicon-rich barrier layer have formed on the interface between the Cr-Si coating and the NiCrA1Y coating. This barrier layer not only prevents aluminum and chromium from diffusing into the substrate, but also impedes the diffusion of other elements from the substrate into the coating. The results also reveal that, for optimal oxidation resistance at 1050°C, the top layer in a multilayered coating should have at least Al/Ni ratio of one; whereas the multilayered coating with the All Ni ratio of two in the top layer exhibits the best oxidation resistance at 1150°C. The DOE methodology provides an excellent means for process optimization and the selection of oxidation test matrix, and also offers a more thorough understanding of the

Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong-Kyu; Im, Yong-Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

2015-04-01

This article proposes an efficient metaheuristic based on hybridization of teaching-learning-based optimization and differential evolution for optimization to improve the flatness of a strip during a strip coiling process. Differential evolution operators were integrated into the teaching-learning-based optimization with a Latin hypercube sampling technique for generation of an initial population. The objective function was introduced to reduce axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love's elastic solution within the thin strip, which may cause an irregular surface profile of the strip during the strip coiling process. The hybrid optimizer and several well-established evolutionary algorithms (EAs) were used to solve the optimization problem. The comparative studies show that the proposed hybrid algorithm outperformed other EAs in terms of convergence rate and consistency. It was found that the proposed hybrid approach was powerful for process optimization, especially with a large-scale design problem.

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Peptide Processing Is Critical for T-Cell Memory Inflation and May Be Optimized to Improve Immune Protection by CMV-Based Vaccine Vectors.

PubMed

Dekhtiarenko, Iryna; Ratts, Robert B; Blatnik, Renata; Lee, Lian N; Fischer, Sonja; Borkner, Lisa; Oduro, Jennifer D; Marandu, Thomas F; Hoppe, Stephanie; Ruzsics, Zsolt; Sonnemann, Julia K; Mansouri, Mandana; Meyer, Christine; Lemmermann, Niels A W; Holtappels, Rafaela; Arens, Ramon; Klenerman, Paul; Früh, Klaus; Reddehase, Matthias J; Riemer, Angelika B; Cicin-Sain, Luka

2016-12-01

Cytomegalovirus (CMV) elicits long-term T-cell immunity of unparalleled strength, which has allowed the development of highly protective CMV-based vaccine vectors. Counterintuitively, experimental vaccines encoding a single MHC-I restricted epitope offered better immune protection than those expressing entire proteins, including the same epitope. To clarify this conundrum, we generated recombinant murine CMVs (MCMVs) encoding well-characterized MHC-I epitopes at different positions within viral genes and observed strong immune responses and protection against viruses and tumor growth when the epitopes were expressed at the protein C-terminus. We used the M45-encoded conventional epitope HGIRNASFI to dissect this phenomenon at the molecular level. A recombinant MCMV expressing HGIRNASFI on the C-terminus of M45, in contrast to wild-type MCMV, enabled peptide processing by the constitutive proteasome, direct antigen presentation, and an inflation of antigen-specific effector memory cells. Consequently, our results indicate that constitutive proteasome processing of antigenic epitopes in latently infected cells is required for robust inflationary responses. This insight allows utilizing the epitope positioning in the design of CMV-based vectors as a novel strategy for enhancing their efficacy.

Peptide Processing Is Critical for T-Cell Memory Inflation and May Be Optimized to Improve Immune Protection by CMV-Based Vaccine Vectors

PubMed Central

Blatnik, Renata; Lee, Lian N.; Fischer, Sonja; Borkner, Lisa; Oduro, Jennifer D.; Marandu, Thomas F.; Hoppe, Stephanie; Ruzsics, Zsolt; Sonnemann, Julia K.; Meyer, Christine; Holtappels, Rafaela; Arens, Ramon; Früh, Klaus; Reddehase, Matthias J.; Riemer, Angelika B.; Cicin-Sain, Luka

2016-01-01

Cytomegalovirus (CMV) elicits long-term T-cell immunity of unparalleled strength, which has allowed the development of highly protective CMV-based vaccine vectors. Counterintuitively, experimental vaccines encoding a single MHC-I restricted epitope offered better immune protection than those expressing entire proteins, including the same epitope. To clarify this conundrum, we generated recombinant murine CMVs (MCMVs) encoding well-characterized MHC-I epitopes at different positions within viral genes and observed strong immune responses and protection against viruses and tumor growth when the epitopes were expressed at the protein C-terminus. We used the M45-encoded conventional epitope HGIRNASFI to dissect this phenomenon at the molecular level. A recombinant MCMV expressing HGIRNASFI on the C-terminus of M45, in contrast to wild-type MCMV, enabled peptide processing by the constitutive proteasome, direct antigen presentation, and an inflation of antigen-specific effector memory cells. Consequently, our results indicate that constitutive proteasome processing of antigenic epitopes in latently infected cells is required for robust inflationary responses. This insight allows utilizing the epitope positioning in the design of CMV-based vectors as a novel strategy for enhancing their efficacy. PMID:27977791

Optimal Design of Material and Process Parameters in Powder Injection Molding

NASA Astrophysics Data System (ADS)

Ayad, G.; Barriere, T.; Gelin, J. C.; Song, J.; Liu, B.

2007-04-01

The paper is concerned with optimization and parametric identification for the different stages in Powder Injection Molding process that consists first in injection of powder mixture with polymer binder and then to the sintering of the resulting powders part by solid state diffusion. In the first part, one describes an original methodology to optimize the process and geometry parameters in injection stage based on the combination of design of experiments and an adaptive Response Surface Modeling. Then the second part of the paper describes the identification strategy that one proposes for the sintering stage, using the identification of sintering parameters from dilatometeric curves followed by the optimization of the sintering process. The proposed approaches are applied to the optimization of material and process parameters for manufacturing a ceramic femoral implant. One demonstrates that the proposed approach give satisfactory results.

Optimization of the production process using virtual model of a workspace

NASA Astrophysics Data System (ADS)

Monica, Z.

2015-11-01

Optimization of the production process is an element of the design cycle consisting of: problem definition, modelling, simulation, optimization and implementation. Without the use of simulation techniques, the only thing which could be achieved is larger or smaller improvement of the process, not the optimization (i.e., the best result it is possible to get for the conditions under which the process works). Optimization is generally management actions that are ultimately bring savings in time, resources, and raw materials and improve the performance of a specific process. It does not matter whether it is a service or manufacturing process. Optimizing the savings generated by improving and increasing the efficiency of the processes. Optimization consists primarily of organizational activities that require very little investment, or rely solely on the changing organization of work. Modern companies operating in a market economy shows a significant increase in interest in modern methods of production management and services. This trend is due to the high competitiveness among companies that want to achieve success are forced to continually modify the ways to manage and flexible response to changing demand. Modern methods of production management, not only imply a stable position of the company in the sector, but also influence the improvement of health and safety within the company and contribute to the implementation of more efficient rules for standardization work in the company. This is why in the paper is presented the application of such developed environment like Siemens NX to create the virtual model of a production system and to simulate as well as optimize its work. The analyzed system is the robotized workcell consisting of: machine tools, industrial robots, conveyors, auxiliary equipment and buffers. In the program could be defined the control program realizing the main task in the virtual workcell. It is possible, using this tool, to optimize both the

Facial protection conferred by cycle safety helmets: use of digitized image processing to develop a new nondestructive test.

PubMed

Harrison, M; Shepherd, J P

1997-07-01

Cycle safety helmets are designed to prevent head injury. Although most commercially available helmets conform to one of several national and international standards, individual designs differ widely, particularly in relation to face coverage. A method was developed to assess the potential for the differing designs to protect the face from injury. A nonimpact test was assessed, using digitized image-processing software (Digithurst Ltd.) to measure the shadow cast by a helmet rim under a collimated plane light source onto the face of a mannequin headform. Twelve helmet designs available internationally were tested and ranked with respect to the direct protection conferred (area of the face directly covered by the helmet) and indirect protection (area of the face shaded). The three highest-ranking helmets for direct protection (Rosebank Stackhat, Asphalt Warrior, and Lazer Voyager) also ranked the highest for indirect protection. These helmets were more inferiorly extended and were of a more bulky construction. It was concluded that the dimensions of cycle helmets in relation to face coverage are crucial in influencing the extent to which facial protection is conferred. International test standards need urgent revision to ensure that face coverage is optimized. Lower-face protection could be achieved through incorporation of a lower-face bar to cycle helmets.

Combined micromechanical and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Mathematical model of information process of protection of the social sector

NASA Astrophysics Data System (ADS)

Novikov, D. A.; Tsarkova, E. G.; Dubrovin, A. S.; Soloviev, A. S.

2018-03-01

In work the mathematical model of information protection of society against distribution of extremist moods by means of impact on mass consciousness of information placed in media is investigated. Internal and external channels on which there is a dissemination of information are designated. The problem of optimization consisting in search of the optimum strategy allowing to use most effectively media for dissemination of antiterrorist information with the minimum financial expenses is solved. The algorithm of a numerical method of the solution of a problem of optimization is constructed and also the analysis of results of a computing experiment is carried out.

Is protection against florivory consistent with the optimal defense hypothesis?

PubMed

Godschalx, Adrienne L; Stady, Lauren; Watzig, Benjamin; Ballhorn, Daniel J

2016-01-28

Plant defense traits require resources and energy that plants may otherwise use for growth and reproduction. In order to most efficiently protect plant tissues from herbivory, one widely accepted assumption of the optimal defense hypothesis states that plants protect tissues most relevant to fitness. Reproductive organs directly determining plant fitness, including flowers and immature fruit, as well as young, productive leaf tissue thus should be particularly well-defended. To test this hypothesis, we quantified the cyanogenic potential (HCNp)-a direct, chemical defense-systemically expressed in vegetative and reproductive organs in lima bean (Phaseolus lunatus), and we tested susceptibility of these organs in bioassays with a generalist insect herbivore, the Large Yellow Underwing (Noctuidae: Noctua pronuba). To determine the actual impact of either florivory (herbivory on flowers) or folivory on seed production as a measure of maternal fitness, we removed varying percentages of total flowers or young leaf tissue and quantified developing fruit, seeds, and seed viability. We found extremely low HCNp in flowers (8.66 ± 2.19 μmol CN(-) g(-1) FW in young, white flowers, 6.23 ± 1.25 μmol CN(-) g(-1) FW in mature, yellow flowers) and in pods (ranging from 32.05 ± 7.08 to 0.09 ± 0.08 μmol CN(-) g(-1) FW in young to mature pods, respectively) whereas young leaves showed high levels of defense (67.35 ± 3.15 μmol CN(-) g(-1) FW). Correspondingly, herbivores consumed more flowers than any other tissue, which, when taken alone, appears to contradict the optimal defense hypothesis. However, experimentally removing flowers did not significantly impact fitness, while leaf tissue removal significantly reduced production of viable seeds. Even though flowers were the least defended and most consumed, our results support the optimal defense hypothesis due to i) the lack of flower removal effects on fitness and ii) the high defense investment in

Hierarchical optimal control of large-scale nonlinear chemical processes.

PubMed

Ramezani, Mohammad Hossein; Sadati, Nasser

2009-01-01

In this paper, a new approach is presented for optimal control of large-scale chemical processes. In this approach, the chemical process is decomposed into smaller sub-systems at the first level, and a coordinator at the second level, for which a two-level hierarchical control strategy is designed. For this purpose, each sub-system in the first level can be solved separately, by using any conventional optimization algorithm. In the second level, the solutions obtained from the first level are coordinated using a new gradient-type strategy, which is updated by the error of the coordination vector. The proposed algorithm is used to solve the optimal control problem of a complex nonlinear chemical stirred tank reactor (CSTR), where its solution is also compared with the ones obtained using the centralized approach. The simulation results show the efficiency and the capability of the proposed hierarchical approach, in finding the optimal solution, over the centralized method.

Mars Soil-Based Resource Processing and Planetary Protection

NASA Technical Reports Server (NTRS)

Sanders, G. B.; Mueller, R. P.

2015-01-01

The ability to extract and process resources at the site of exploration into products and services, commonly referred to as In Situ Resource Utilization (ISRU), can have significant benefits for robotic and human exploration missions. In particular, the ability to use in situ resources to make propellants, fuel cell reactants, and life support consumables has been shown in studies to significantly reduce mission mass, cost, and risk, while enhancing or enabling missions not possible without the incorporation of ISRU. In December 2007, NASA completed the Mars Human Design Reference Architecture (DRA) 5.0 study. For the first time in a large scale Mars architecture study, water from Mars soil was considered as a potential resource. At the time of the study, knowledge of water resources (their form, concentration, and distribution) was extremely limited. Also, due to lack of understanding of how to apply planetary protection rules and requirements to ISRU soil-based excavation and processing, an extremely conservative approach was incorporated where only the top several centimeters of ultraviolet (UV) radiated soil could be processed (assumed to be 3% water by mass). While results of the Mars DRA 5.0 study showed that combining atmosphere processing to make oxygen and methane with soil processing to extract water provided the lowest mission mass, atmosphere processing to convert carbon dioxide (CO2) into oxygen was baselined for the mission since it was the lowest power and risk option. With increased knowledge and further clarification of Mars planetary protection rules, and the recent release of the Mars Exploration Program Analysis Group (MEPAG) report on "Special Regions and the Human Exploration of Mars", it is time to reexamine potential water resources on Mars, options for soil processing to extract water, and the implications with respect to planetary protection and Special Regions on Mars.

Traffic protection in MPLS networks using an off-line flow optimization model

NASA Astrophysics Data System (ADS)

Krzesinski, Anthony E.; Muller, Karen E.

2002-07-01

MPLS-based recovery is intended to effect rapid and complete restoration of traffic affected by a fault in an MPLS network. Two MPLS-based recovery models have been proposed: IP re-routing which establishes recovery paths on demand, and protection switching which works with pre-established recovery paths. IP re-routing is robust and frugal since no resources are pre-committed but is inherently slower than protection switching which is intended to offer high reliability to premium services where fault recovery takes place at the 100 ms time scale. We present a model of protection switching in MPLS networks. A variant of the flow deviation method is used to find and capacitate a set of optimal label switched paths. The traffic is routed over a set of working LSPs. Global repair is implemented by reserving a set of pre-established recovery LSPs. An analytic model is used to evaluate the MPLS-based recovery mechanisms in response to bi-directional link failures. A simulation model is used to evaluate the MPLS recovery cycle in terms of the time needed to restore the traffic after a uni-directional link failure. The models are applied to evaluate the effectiveness of protection switching in networks consisting of between 20 and 100 nodes.

UHPC for Blast and Ballistic Protection, Explosion Testing and Composition Optimization

NASA Astrophysics Data System (ADS)

Bibora, P.; Drdlová, M.; Prachař, V.; Sviták, O.

2017-10-01

The realization of high performance concrete resistant to detonation is the aim and expected outcome of the presented project, which is oriented to development of construction materials for larger objects as protective walls and bunkers. Use of high-strength concrete (HSC / HPC - “high strength / performance concrete”) and high-fiber reinforced concrete (UHPC / UHPFC -“Ultra High Performance Fiber Reinforced Concrete”) seems to be optimal for this purpose of research. The paper describes the research phase of the project, in which we focused on the selection of specific raw materials and chemical additives, including determining the most suitable type and amount of distributed fiber reinforcement. Composition of UHPC was optimized during laboratory manufacture of test specimens to obtain the best desired physical- mechanical properties of developed high performance concretes. In connection with laboratory testing, explosion field tests of UHPC specimens were performed and explosion resistance of laboratory produced UHPC testing boards was investigated.

Cyclically optimized electrochemical processes

NASA Astrophysics Data System (ADS)

Ruedisueli, Robert Louis

It has been frequently observed in experiment and industry practice that electrochemical processes (deposition, dissolution, fuel cells) operated in an intermittent or cyclic (AC) mode show improvements in efficiency and/or quality and yield over their steady (DC) mode of operation. Whether rationally invoked by design or empirically tuned-in, the optimal operating frequency and duty cycle is dependent upon the dominant relaxation time constant for the process in question. The electrochemical relaxation time constant is a function of: double-layer and reaction intermediary pseudo-capacitances, ion (charge) transport via electrical migration (mobility), and diffusion across a concentration gradient to electrode surface reaction sites where charge transfer and species incorporation or elimination occurs. The rate determining step dominates the time constant for the reaction or process. Electrochemical impedance spectroscopy (EIS) and piezoelectric crystal electrode (PCE) response analysis have proven to be useful tools in the study and identification of reaction mechanisms. This work explains and demonstrates with the electro-deposition of copper the application of EIS and PCE measurement and analysis to the selection of an optimum cyclic operating schedule, an optimum driving frequency for efficient, sustained cyclic (pulsed) operation.

Optimization of the Bridgman crystal growth process

NASA Astrophysics Data System (ADS)

Margulies, M.; Witomski, P.; Duffar, T.

2004-05-01

A numerical optimization method of the vertical Bridgman growth configuration is presented and developed. It permits to optimize the furnace temperature field and the pulling rate versus time in order to decrease the radial thermal gradients in the sample. Some constraints are also included in order to insure physically realistic results. The model includes the two classical non-linearities associated to crystal growth processes, the radiative thermal exchange and the release of latent heat at the solid-liquid interface. The mathematical analysis and development of the problem is shortly described. On some examples, it is shown that the method works in a satisfactory way; however the results are dependent on the numerical parameters. Improvements of the optimization model, on the physical and numerical point of view, are suggested.

Production of Low Cost Carbon-Fiber through Energy Optimization of Stabilization Process.

PubMed

Golkarnarenji, Gelayol; Naebe, Minoo; Badii, Khashayar; Milani, Abbas S; Jazar, Reza N; Khayyam, Hamid

2018-03-05

To produce high quality and low cost carbon fiber-based composites, the optimization of the production process of carbon fiber and its properties is one of the main keys. The stabilization process is the most important step in carbon fiber production that consumes a large amount of energy and its optimization can reduce the cost to a large extent. In this study, two intelligent optimization techniques, namely Support Vector Regression (SVR) and Artificial Neural Network (ANN), were studied and compared, with a limited dataset obtained to predict physical property (density) of oxidative stabilized PAN fiber (OPF) in the second zone of a stabilization oven within a carbon fiber production line. The results were then used to optimize the energy consumption in the process. The case study can be beneficial to chemical industries involving carbon fiber manufacturing, for assessing and optimizing different stabilization process conditions at large.

Production of Low Cost Carbon-Fiber through Energy Optimization of Stabilization Process

PubMed Central

Golkarnarenji, Gelayol; Naebe, Minoo; Badii, Khashayar; Milani, Abbas S.; Jazar, Reza N.; Khayyam, Hamid

2018-01-01

To produce high quality and low cost carbon fiber-based composites, the optimization of the production process of carbon fiber and its properties is one of the main keys. The stabilization process is the most important step in carbon fiber production that consumes a large amount of energy and its optimization can reduce the cost to a large extent. In this study, two intelligent optimization techniques, namely Support Vector Regression (SVR) and Artificial Neural Network (ANN), were studied and compared, with a limited dataset obtained to predict physical property (density) of oxidative stabilized PAN fiber (OPF) in the second zone of a stabilization oven within a carbon fiber production line. The results were then used to optimize the energy consumption in the process. The case study can be beneficial to chemical industries involving carbon fiber manufacturing, for assessing and optimizing different stabilization process conditions at large. PMID:29510592

When teams shift among processes: insights from simulation and optimization.

PubMed

Kennedy, Deanna M; McComb, Sara A

2014-09-01

This article introduces process shifts to study the temporal interplay among transition and action processes espoused in the recurring phase model proposed by Marks, Mathieu, and Zacarro (2001). Process shifts are those points in time when teams complete a focal process and change to another process. By using team communication patterns to measure process shifts, this research explores (a) when teams shift among different transition processes and initiate action processes and (b) the potential of different interventions, such as communication directives, to manipulate process shift timing and order and, ultimately, team performance. Virtual experiments are employed to compare data from observed laboratory teams not receiving interventions, simulated teams receiving interventions, and optimal simulated teams generated using genetic algorithm procedures. Our results offer insights about the potential for different interventions to affect team performance. Moreover, certain interventions may promote discussions about key issues (e.g., tactical strategies) and facilitate shifting among transition processes in a manner that emulates optimal simulated teams' communication patterns. Thus, we contribute to theory regarding team processes in 2 important ways. First, we present process shifts as a way to explore the timing of when teams shift from transition to action processes. Second, we use virtual experimentation to identify those interventions with the greatest potential to affect performance by changing when teams shift among processes. Additionally, we employ computational methods including neural networks, simulation, and optimization, thereby demonstrating their applicability in conducting team research. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Considerations on the Optimal and Efficient Processing of Information-Bearing Signals

ERIC Educational Resources Information Center

Harms, Herbert Andrew

2013-01-01

Noise is a fundamental hurdle that impedes the processing of information-bearing signals, specifically the extraction of salient information. Processing that is both optimal and efficient is desired; optimality ensures the extracted information has the highest fidelity allowed by the noise, while efficiency ensures limited resource usage. Optimal…

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

Optimization and Improvement of Test Processes on a Production Line

NASA Astrophysics Data System (ADS)

Sujová, Erika; Čierna, Helena

2018-06-01

The paper deals with increasing processes efficiency at a production line of cylinder heads of engines in a production company operating in the automotive industry. The goal is to achieve improvement and optimization of test processes on a production line. It analyzes options for improving capacity, availability and productivity of processes of an output test by using modern technology available on the market. We have focused on analysis of operation times before and after optimization of test processes at specific production sections. By analyzing measured results we have determined differences in time before and after improvement of the process. We have determined a coefficient of efficiency OEE and by comparing outputs we have confirmed real improvement of the process of the output test of cylinder heads.

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

NASA Astrophysics Data System (ADS)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

Intracellular response to process optimization and impact on productivity and product aggregates for a high-titer CHO cell process.

PubMed

Handlogten, Michael W; Lee-O'Brien, Allison; Roy, Gargi; Levitskaya, Sophia V; Venkat, Raghavan; Singh, Shailendra; Ahuja, Sanjeev

2018-01-01

A key goal in process development for antibodies is to increase productivity while maintaining or improving product quality. During process development of an antibody, titers were increased from 4 to 10 g/L while simultaneously decreasing aggregates. Process development involved optimization of media and feed formulations, feed strategy, and process parameters including pH and temperature. To better understand how CHO cells respond to process changes, the changes were implemented in a stepwise manner. The first change was an optimization of the feed formulation, the second was an optimization of the medium, and the third was an optimization of process parameters. Multiple process outputs were evaluated including cell growth, osmolality, lactate production, ammonium concentration, antibody production, and aggregate levels. Additionally, detailed assessment of oxygen uptake, nutrient and amino acid consumption, extracellular and intracellular redox environment, oxidative stress, activation of the unfolded protein response (UPR) pathway, protein disulfide isomerase (PDI) expression, and heavy and light chain mRNA expression provided an in-depth understanding of the cellular response to process changes. The results demonstrate that mRNA expression and UPR activation were unaffected by process changes, and that increased PDI expression and optimized nutrient supplementation are required for higher productivity processes. Furthermore, our findings demonstrate the role of extra- and intracellular redox environment on productivity and antibody aggregation. Processes using the optimized medium, with increased concentrations of redox modifying agents, had the highest overall specific productivity, reduced aggregate levels, and helped cells better withstand the high levels of oxidative stress associated with increased productivity. Specific productivities of different processes positively correlated to average intracellular values of total glutathione. Additionally

Stress Exposure and Depression in Disadvantaged Women: The Protective Effects of Optimism and Perceived Control

ERIC Educational Resources Information Center

Grote, Nancy K.; Bledsoe, Sarah E.; Larkin, Jill; Lemay, Edward P., Jr.; Brown, Charlotte

2007-01-01

In the present study, the authors predicted that the individual protective factors of optimism and perceived control over acute and chronic stressors would buffer the relations between acute and chronic stress exposure and severity of depression, controlling for household income, in a sample of financially disadvantaged women. Ninety-seven African…

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Improving processes through evolutionary optimization.

PubMed

Clancy, Thomas R

2011-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

Application of a neural network to simulate analysis in an optimization process

NASA Technical Reports Server (NTRS)

Rogers, James L.; Lamarsh, William J., II

1992-01-01

A new experimental software package called NETS/PROSSS aimed at reducing the computing time required to solve a complex design problem is described. The software combines a neural network for simulating the analysis program with an optimization program. The neural network is applied to approximate results of a finite element analysis program to quickly obtain a near-optimal solution. Results of the NETS/PROSSS optimization process can also be used as an initial design in a normal optimization process and make it possible to converge to an optimum solution with significantly fewer iterations.

Multi-objective optimization model of CNC machining to minimize processing time and environmental impact

NASA Astrophysics Data System (ADS)

Hamada, Aulia; Rosyidi, Cucuk Nur; Jauhari, Wakhid Ahmad

2017-11-01

Minimizing processing time in a production system can increase the efficiency of a manufacturing company. Processing time are influenced by application of modern technology and machining parameter. Application of modern technology can be apply by use of CNC machining, one of the machining process can be done with a CNC machining is turning. However, the machining parameters not only affect the processing time but also affect the environmental impact. Hence, optimization model is needed to optimize the machining parameters to minimize the processing time and environmental impact. This research developed a multi-objective optimization to minimize the processing time and environmental impact in CNC turning process which will result in optimal decision variables of cutting speed and feed rate. Environmental impact is converted from environmental burden through the use of eco-indicator 99. The model were solved by using OptQuest optimization software from Oracle Crystal Ball.

Does high optimism protect against the inter-generational transmission of high BMI? The Cardiovascular Risk in Young Finns Study.

PubMed

Serlachius, Anna; Pulkki-Råback, Laura; Juonala, Markus; Sabin, Matthew; Lehtimäki, Terho; Raitakari, Olli; Elovainio, Marko

2017-09-01

The transmission of overweight from one generation to the next is well established, however little is known about what psychosocial factors may protect against this familial risk. The aim of this study was to examine whether optimism plays a role in the intergenerational transmission of obesity. Our sample included 1043 participants from the prospective Cardiovascular Risk in Young FINNS Study. Optimism was measured in early adulthood (2001) when the cohort was aged 24-39years. BMI was measured in 2001 (baseline) and 2012 when they were aged 35-50years. Parental BMI was measured in 1980. Hierarchical linear regression and logistic regression were used to examine the association between optimism and future BMI/obesity, and whether an interaction existed between optimism and parental BMI when predicting BMI/obesity 11years later. High optimism in young adulthood demonstrated a negative relationship with high BMI in mid-adulthood, but only in women (β=-0.127, p=0.001). The optimism×maternal BMI interaction term was a significant predictor of future BMI in women (β=-0.588, p=0.036). The logistic regression results confirmed that high optimism predicted reduced obesity in women (OR=0.68, 95% CI, 0.55-0.86), however the optimism × maternal obesity interaction term was not a significant predictor (OR=0.50, 95% CI, 0.10-2.48). Our findings supported our hypothesis that high optimism mitigated the intergenerational transmission of high BMI, but only in women. These findings also provided evidence that positive psychosocial factors such as optimism are associated with long-term protective effects on BMI in women. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimizing The DSSC Fabrication Process Using Lean Six Sigma

NASA Astrophysics Data System (ADS)

Fauss, Brian

Alternative energy technologies must become more cost effective to achieve grid parity with fossil fuels. Dye sensitized solar cells (DSSCs) are an innovative third generation photovoltaic technology, which is demonstrating tremendous potential to become a revolutionary technology due to recent breakthroughs in cost of fabrication. The study here focused on quality improvement measures undertaken to improve fabrication of DSSCs and enhance process efficiency and effectiveness. Several quality improvement methods were implemented to optimize the seven step individual DSSC fabrication processes. Lean Manufacturing's 5S method successfully increased efficiency in all of the processes. Six Sigma's DMAIC methodology was used to identify and eliminate each of the root causes of defects in the critical titanium dioxide deposition process. These optimizations resulted with the following significant improvements in the production process: 1. fabrication time of the DSSCs was reduced by 54 %; 2. fabrication procedures were improved to the extent that all critical defects in the process were eliminated; 3. the quantity of functioning DSSCs fabricated was increased from 17 % to 90 %.

Preparation of Acute Brain Slices Using an Optimized N-Methyl-D-glucamine Protective Recovery Method.

PubMed

Ting, Jonathan T; Lee, Brian R; Chong, Peter; Soler-Llavina, Gilberto; Cobbs, Charles; Koch, Christof; Zeng, Hongkui; Lein, Ed

2018-02-26

This protocol is a practical guide to the N-methyl-D-glucamine (NMDG) protective recovery method of brain slice preparation. Numerous recent studies have validated the utility of this method for enhancing neuronal preservation and overall brain slice viability. The implementation of this technique by early adopters has facilitated detailed investigations into brain function using diverse experimental applications and spanning a wide range of animal ages, brain regions, and cell types. Steps are outlined for carrying out the protective recovery brain slice technique using an optimized NMDG artificial cerebrospinal fluid (aCSF) media formulation and enhanced procedure to reliably obtain healthy brain slices for patch clamp electrophysiology. With this updated approach, a substantial improvement is observed in the speed and reliability of gigaohm seal formation during targeted patch clamp recording experiments while maintaining excellent neuronal preservation, thereby facilitating challenging experimental applications. Representative results are provided from multi-neuron patch clamp recording experiments to assay synaptic connectivity in neocortical brain slices prepared from young adult transgenic mice and mature adult human neurosurgical specimens. Furthermore, the optimized NMDG protective recovery method of brain slicing is compatible with both juvenile and adult animals, thus resolving a limitation of the original methodology. In summary, a single media formulation and brain slicing procedure can be implemented across various species and ages to achieve excellent viability and tissue preservation.

Preparation of Acute Brain Slices Using an Optimized N-Methyl-D-glucamine Protective Recovery Method

PubMed Central

Chong, Peter; Soler-Llavina, Gilberto; Cobbs, Charles; Koch, Christof; Zeng, Hongkui; Lein, Ed

2018-01-01

This protocol is a practical guide to the N-methyl-D-glucamine (NMDG) protective recovery method of brain slice preparation. Numerous recent studies have validated the utility of this method for enhancing neuronal preservation and overall brain slice viability. The implementation of this technique by early adopters has facilitated detailed investigations into brain function using diverse experimental applications and spanning a wide range of animal ages, brain regions, and cell types. Steps are outlined for carrying out the protective recovery brain slice technique using an optimized NMDG artificial cerebrospinal fluid (aCSF) media formulation and enhanced procedure to reliably obtain healthy brain slices for patch clamp electrophysiology. With this updated approach, a substantial improvement is observed in the speed and reliability of gigaohm seal formation during targeted patch clamp recording experiments while maintaining excellent neuronal preservation, thereby facilitating challenging experimental applications. Representative results are provided from multi-neuron patch clamp recording experiments to assay synaptic connectivity in neocortical brain slices prepared from young adult transgenic mice and mature adult human neurosurgical specimens. Furthermore, the optimized NMDG protective recovery method of brain slicing is compatible with both juvenile and adult animals, thus resolving a limitation of the original methodology. In summary, a single media formulation and brain slicing procedure can be implemented across various species and ages to achieve excellent viability and tissue preservation. PMID:29553547

[Legal aspects of prevention. The constitutional principle of optimal health protection].

PubMed

von Wartburg, W P

1978-12-01

With respect to the health services, a State founded upon the rule of law is in duty bound to act with restraint. Its aim should be to guarantee that public health is maintained in optimal fashion. For this purpose it must endeavour to exert an effective influence on environmental factors. The three main categories of activity with which the health services are concerned, i.e. protection of health, promotion of health, and health care should be governed by the principles inherent in a State based upon the rule of law. As regards preventive measures, this means that the State has to shape the environment and society in such a way as to meet the requirements of a modern system for the protection of public health, its objective in this context being to eliminate or minimise health risks. A rational government programme for the promotion of public health must also be designed to promote a more health-conscious pattern of behaviour in the population at large and to encourage those citizens requiring treatment to invoke the aid of the health care services without delay.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Concurrent micromechanical tailoring and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, Christos C.

1990-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Psychometric assessment of the processes of change scale for sun protection.

PubMed

Sillice, Marie A; Babbin, Steven F; Redding, Colleen A; Rossi, Joseph S; Paiva, Andrea L; Velicer, Wayne F

2018-01-01

The fourteen-factor Processes of Change Scale for Sun Protection assesses behavioral and experiential strategies that underlie the process of sun protection acquisition and maintenance. Variations of this measure have been used effectively in several randomized sun protection trials, both for evaluation and as a basis for intervention. However, there are no published studies, to date, that evaluate the psychometric properties of the scale. The present study evaluated factorial invariance and scale reliability in a national sample (N = 1360) of adults involved in a Transtheoretical model tailored intervention for exercise and sun protection, at baseline. Invariance testing ranged from least to most restrictive: Configural Invariance (constraints only factor structure and zero loadings); Pattern Identity Invariance (equal factor loadings across target groups); and Strong Factorial Invariance (equal factor loadings and measurement errors). Multi-sample structural equation modeling tested the invariance of the measurement model across seven subgroups: age, education, ethnicity, gender, race, skin tone, and Stage of Change for Sun Protection. Strong factorial invariance was found across all subgroups. Internal consistency coefficient Alpha and factor rho reliability, respectively, were .83 and .80 for behavioral processes, .91 and .89 for experiential processes, and .93 and .91 for the global scale. These results provide strong empirical evidence that the scale is consistent, has internal validity and can be used in research interventions with population-based adult samples.

The protective role of maternal post-traumatic growth and cognitive trauma processing in Palestinian mothers and infants: a longitudinal study.

PubMed

Diab, Safwat Y; Isosävi, Sanna; Qouta, Samir R; Kuittinen, Saija; Punamäki, Raija-Leena

2018-02-21

Women at pre partum and post partum are especially susceptible to war trauma because they struggle to protect their infants from danger. Trauma research suggests increased problems in maternal mental health and infant development. Yet many cognitive-emotional processes affect the trauma survivors' mental health, such as post-traumatic growth and post-traumatic cognition. The aim of this study was to examine whether a mother's high post-traumatic growth and optimal post-traumatic cognition could protect their own mental health and their infant's stress regulation from the effects of traumatic war experiences. This three-wave prospective study involved Palestinian women living in the Gaza Strip who were at the second trimester of pregnancy (T1), women with infants aged 4 months (T2), and women with children aged 12 months (T3) months. The participants reported their war experiences in a 30-item checklist of losses, destruction, and atrocities in the 2008-09, 2012, and 2014 military offensives. Post-traumatic growth was assessed by a 21-item scale and post-traumatic cognition by a 36-item scale. Maternal mental health was assessed by post-traumatic stress disorder (PTSD), depressive, anxiety, and dissociation symptoms at T1 and T3, and infants' stress regulation was assessed with the Infant Behaviour Questionnaire at T2 and T3. We included 511 women at T1, 481 women at T2, and 454 women at T3. High maternal post-traumatic growth and post-traumatic cognition had protective roles. Post-traumatic growth had a protective effect on maternal mental health since severe exposure to traumatic war experiences was not associated with maternal PTSD, depression, and dissociation if women showed high post-traumatic growth, as indicated by the significant interaction effect between post-traumatic growth and war trauma on each of the three symptoms. Post-traumatic cognition had a protective effect on infant development since severe exposure was not associated with dysfunctional

Video enhancement method with color-protection post-processing

NASA Astrophysics Data System (ADS)

Kim, Youn Jin; Kwak, Youngshin

2015-01-01

The current study is aimed to propose a post-processing method for video enhancement by adopting a color-protection technique. The color-protection intends to attenuate perceptible artifacts due to over-enhancements in visually sensitive image regions such as low-chroma colors, including skin and gray objects. In addition, reducing the loss in color texture caused by the out-of-color-gamut signals is also taken into account. Consequently, color reproducibility of video sequences could be remarkably enhanced while the undesirable visual exaggerations are minimized.

Optimal Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

Optimal diabatic dynamics of Majorana-based quantum gates

NASA Astrophysics Data System (ADS)

Rahmani, Armin; Seradjeh, Babak; Franz, Marcel

2017-08-01

In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and 1 /f (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.

Efficient Robust Optimization of Metal Forming Processes using a Sequential Metamodel Based Strategy

NASA Astrophysics Data System (ADS)

Wiebenga, J. H.; Klaseboer, G.; van den Boogaard, A. H.

2011-08-01

The coupling of Finite Element (FE) simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a new and generally applicable structured methodology for modeling and solving robust optimization problems. Stochastic design variables or noise variables are taken into account explicitly in the optimization procedure. The metamodel-based strategy is combined with a sequential improvement algorithm to efficiently increase the accuracy of the objective function prediction. This is only done at regions of interest containing the optimal robust design. Application of the methodology to an industrial V-bending process resulted in valuable process insights and an improved robust process design. Moreover, a significant improvement of the robustness (>2σ) was obtained by minimizing the deteriorating effects of several noise variables. The robust optimization results demonstrate the general applicability of the robust optimization strategy and underline the importance of including uncertainty and robustness explicitly in the numerical optimization procedure.

Optimizing product life cycle processes in design phase

NASA Astrophysics Data System (ADS)

Faneye, Ola. B.; Anderl, Reiner

2002-02-01

Life cycle concepts do not only serve as basis in assisting product developers understand the dependencies between products and their life cycles, they also help in identifying potential opportunities for improvement in products. Common traditional concepts focus mainly on energy and material flow across life phases, necessitating the availability of metrics derived from a reference product. Knowledge of life cycle processes won from an existing product is directly reused in its redesign. Depending on sales volume nevertheless, the environmental impact before product optimization can be substantial. With modern information technologies today, computer-aided life cycle methodologies can be applied well before product use. On the basis of a virtual prototype, life cycle processes are analyzed and optimized, using simulation techniques. This preventive approach does not only help in minimizing (or even eliminating) environmental burdens caused by product, costs incurred due to changes in real product can also be avoided. The paper highlights the relationship between product and life cycle and presents a computer-based methodology for optimizing the product life cycle during design, as presented by SFB 392: Design for Environment - Methods and Tools at Technical University, Darmstadt.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

NASA Astrophysics Data System (ADS)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic processes.

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Computational techniques for design optimization of thermal protective systems for the space shuttle vehicle. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

1971-01-01

A modular program for design optimization of thermal protection systems is discussed. Its capabilities and limitations are reviewed. Instructions for the operation of the program, output, and the program itself are given.

[Optimization of Energy Saving Measures with ABR-MBR Integrated Process].

PubMed

Wu, Peng; Lu, Shuang-jun; Xu, Yue-zhong; Liu, Jie; Shen, Yao-liang

2015-08-01

High energy consumption and membrane fouling are important factors that limit the wide use of membrane bioreactor (MBR). In order to reduce energy consumption and delay the process of membrane fouling, the process of anaerobic baffled reactor (ABR)-MBR was used to treat domestic sewage. The structure of the process and conditions of nitrogen and phosphorus removal were optimized in this study. The results showed that energy consumption was reduced by 43% through optimizing the structure of ABR-MBR process. Meanwhile, the process achieved a high level of COD, NH: -N, TN and TP removal, with the average removal efficiencies of 91%, 85%, 76% and 86%, respectively. In addition, the added particulate media could effectively delay membrane fouling, while the formation process of membrane fouling was changed. The extracted amount of carbohydrates increased while the amount of proteins decreased. Finally, the potential was enhanced for the practical application of MBR.

Optimization process in helicopter design

NASA Technical Reports Server (NTRS)

Logan, A. H.; Banerjee, D.

1984-01-01

In optimizing a helicopter configuration, Hughes Helicopters uses a program called Computer Aided Sizing of Helicopters (CASH), written and updated over the past ten years, and used as an important part of the preliminary design process of the AH-64. First, measures of effectiveness must be supplied to define the mission characteristics of the helicopter to be designed. Then CASH allows the designer to rapidly and automatically develop the basic size of the helicopter (or other rotorcraft) for the given mission. This enables the designer and management to assess the various tradeoffs and to quickly determine the optimum configuration.

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

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

Ampomah, William; Balch, Robert; Will, Robert

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parametersmore » as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

DOE PAGES

Ampomah, William; Balch, Robert; Will, Robert; ...

2017-07-01

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parametersmore » as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about

Laser Cladding of TiAl Intermetallic Alloy on Ti6Al4V -Process Optimization and Properties

NASA Astrophysics Data System (ADS)

Cárcel, B.; Serrano, A.; Zambrano, J.; Amigó, V.; Cárcel, A. C.

In order to improve Ti6Al4V high-temperature resistance and its tribological properties, the deposition of TiAl intermetallic (Ti-48Al-2Cr-2Nb) coating on a Ti6Al4V substrate by coaxial laser cladding has been investigated. Laser cladding by powder injection is an emerging laser material processing technique that allows the deposition of thick protective coatings on substrates,using a high power laser beam as heat source. Laser cladding is a multiple-parameter-dependent process. The main process parameters involved (laser power, powder feeding rate, scanning speed and preheating temperature) has been optimized. The microstructure and geometrical quantities (clad area and dilution) of the coating was characterized by optical microscopy and scanning electron microscopy (SEM). In addition the cooling rate of the clad during the process was measured by a dual-color pyrometer. This result has been related to defectology and mechanical coating properties.

Process for producing radiation-induced self-terminating protective coatings on a substrate

DOEpatents

Klebanoff, Leonard E.

2001-01-01

A gas and radiation are used to produce a protective coating that is substantially void-free on the molecular scale, self-terminating, and degradation resistant. The process can be used to deposit very thin (.apprxeq.5-20 .ANG.) coatings on critical surfaces needing protection from degradative processes including, corrosion and contamination.

Discovering naturally processed antigenic determinants that confer protective T cell immunity

PubMed Central

Gilchuk, Pavlo; Spencer, Charles T.; Conant, Stephanie B.; Hill, Timothy; Gray, Jennifer J.; Niu, Xinnan; Zheng, Mu; Erickson, John J.; Boyd, Kelli L.; McAfee, K. Jill; Oseroff, Carla; Hadrup, Sine R.; Bennink, Jack R.; Hildebrand, William; Edwards, Kathryn M.; Crowe, James E.; Williams, John V.; Buus, Søren; Sette, Alessandro; Schumacher, Ton N.M.; Link, Andrew J.; Joyce, Sebastian

2013-01-01

CD8+ T cells (TCD8) confer protective immunity against many infectious diseases, suggesting that microbial TCD8 determinants are promising vaccine targets. Nevertheless, current T cell antigen identification approaches do not discern which epitopes drive protective immunity during active infection — information that is critical for the rational design of TCD8-targeted vaccines. We employed a proteomics-based approach for large-scale discovery of naturally processed determinants derived from a complex pathogen, vaccinia virus (VACV), that are presented by the most frequent representatives of four major HLA class I supertypes. Immunologic characterization revealed that many previously unidentified VACV determinants were recognized by smallpox-vaccinated human peripheral blood cells in a variegated manner. Many such determinants were recognized by HLA class I–transgenic mouse immune TCD8 too and elicited protective TCD8 immunity against lethal intranasal VACV infection. Notably, efficient processing and stable presentation of immune determinants as well as the availability of naive TCD8 precursors were sufficient to drive a multifunctional, protective TCD8 response. Our approach uses fundamental insights into T cell epitope processing and presentation to define targets of protective TCD8 immunity within human pathogens that have complex proteomes, suggesting that this approach has general applicability in vaccine sciences. PMID:23543059

Discovering naturally processed antigenic determinants that confer protective T cell immunity.

PubMed

Gilchuk, Pavlo; Spencer, Charles T; Conant, Stephanie B; Hill, Timothy; Gray, Jennifer J; Niu, Xinnan; Zheng, Mu; Erickson, John J; Boyd, Kelli L; McAfee, K Jill; Oseroff, Carla; Hadrup, Sine R; Bennink, Jack R; Hildebrand, William; Edwards, Kathryn M; Crowe, James E; Williams, John V; Buus, Søren; Sette, Alessandro; Schumacher, Ton N M; Link, Andrew J; Joyce, Sebastian

2013-05-01

CD8+ T cells (TCD8) confer protective immunity against many infectious diseases, suggesting that microbial TCD8 determinants are promising vaccine targets. Nevertheless, current T cell antigen identification approaches do not discern which epitopes drive protective immunity during active infection - information that is critical for the rational design of TCD8-targeted vaccines. We employed a proteomics-based approach for large-scale discovery of naturally processed determinants derived from a complex pathogen, vaccinia virus (VACV), that are presented by the most frequent representatives of four major HLA class I supertypes. Immunologic characterization revealed that many previously unidentified VACV determinants were recognized by smallpox-vaccinated human peripheral blood cells in a variegated manner. Many such determinants were recognized by HLA class I-transgenic mouse immune TCD8 too and elicited protective TCD8 immunity against lethal intranasal VACV infection. Notably, efficient processing and stable presentation of immune determinants as well as the availability of naive TCD8 precursors were sufficient to drive a multifunctional, protective TCD8 response. Our approach uses fundamental insights into T cell epitope processing and presentation to define targets of protective TCD8 immunity within human pathogens that have complex proteomes, suggesting that this approach has general applicability in vaccine sciences.

Energy-saving management modelling and optimization for lead-acid battery formation process

NASA Astrophysics Data System (ADS)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

A method of network topology optimization design considering application process characteristic

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

Optimization of the Switch Mechanism in a Circuit Breaker Using MBD Based Simulation

PubMed Central

Jang, Jin-Seok; Yoon, Chang-Gyu; Ryu, Chi-Young; Kim, Hyun-Woo; Bae, Byung-Tae; Yoo, Wan-Suk

2015-01-01

A circuit breaker is widely used to protect electric power system from fault currents or system errors; in particular, the opening mechanism in a circuit breaker is important to protect current overflow in the electric system. In this paper, multibody dynamic model of a circuit breaker including switch mechanism was developed including the electromagnetic actuator system. Since the opening mechanism operates sequentially, optimization of the switch mechanism was carried out to improve the current breaking time. In the optimization process, design parameters were selected from length and shape of each latch, which changes pivot points of bearings to shorten the breaking time. To validate optimization results, computational results were compared to physical tests with a high speed camera. Opening time of the optimized mechanism was decreased by 2.3 ms, which was proved by experiments. Switch mechanism design process can be improved including contact-latch system by using this process. PMID:25918740

SPOT: Optimization Tool for Network Adaptable Security

NASA Astrophysics Data System (ADS)

Ksiezopolski, Bogdan; Szalachowski, Pawel; Kotulski, Zbigniew

Recently we have observed the growth of the intelligent application especially with its mobile character, called e-anything. The implementation of these applications provides guarantee of security requirements of the cryptographic protocols which are used in the application. Traditionally the protocols have been configured with the strongest possible security mechanisms. Unfortunately, when the application is used by means of the mobile devices, the strongest protection can lead to the denial of services for them. The solution of this problem is introducing the quality of protection models which will scale the protection level depending on the actual threat level. In this article we would like to introduce the application which manages the protection level of the processes in the mobile environment. The Security Protocol Optimizing Tool (SPOT) optimizes the cryptographic protocol and defines the protocol version appropriate to the actual threat level. In this article the architecture of the SPOT is presented with a detailed description of the included modules.

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.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining.

PubMed

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously.

Optimization process planning using hybrid genetic algorithm and intelligent search for job shop machining

PubMed Central

Salehi, Mojtaba

2010-01-01

Optimization of process planning is considered as the key technology for computer-aided process planning which is a rather complex and difficult procedure. A good process plan of a part is built up based on two elements: (1) the optimized sequence of the operations of the part; and (2) the optimized selection of the machine, cutting tool and Tool Access Direction (TAD) for each operation. In the present work, the process planning is divided into preliminary planning, and secondary/detailed planning. In the preliminary stage, based on the analysis of order and clustering constraints as a compulsive constraint aggregation in operation sequencing and using an intelligent searching strategy, the feasible sequences are generated. Then, in the detailed planning stage, using the genetic algorithm which prunes the initial feasible sequences, the optimized operation sequence and the optimized selection of the machine, cutting tool and TAD for each operation based on optimization constraints as an additive constraint aggregation are obtained. The main contribution of this work is the optimization of sequence of the operations of the part, and optimization of machine selection, cutting tool and TAD for each operation using the intelligent search and genetic algorithm simultaneously. PMID:21845020

Electrochemical properties in a seawater environment of 5456-H116 aluminum alloy subjected to optimal friction stir processing

NASA Astrophysics Data System (ADS)

Park, Jae-Cheul; Kim, Seong-Jong

2010-05-01

The mechanical properties of aluminum alloy may be enhanced by modifying the microstructure of the metal by friction stir processing (FSP). Previous studies have demonstrated that the mechanical characteristics of 5456-H116 Al alloy subjected to FSP, at 250 rpm and 15 mm min-1 using a full screw probe, are similar to those of the original alloy. In the present work, the same alloy was processed under these optimal conditions, and the range of favorable protection potentials with regard to hydrogen embrittlement and stress corrosion cracking was determined to lie between -1.3 and -0.7 V (versus Ag/AgCl). The electrochemical behavior of the specimens subjected to FSP was superior to that of the original 5456-H116 Al alloy.

Development of an Optimization Methodology for the Aluminum Alloy Wheel Casting Process

NASA Astrophysics Data System (ADS)

Duan, Jianglan; Reilly, Carl; Maijer, Daan M.; Cockcroft, Steve L.; Phillion, Andre B.

2015-08-01

An optimization methodology has been developed for the aluminum alloy wheel casting process. The methodology is focused on improving the timing of cooling processes in a die to achieve improved casting quality. This methodology utilizes (1) a casting process model, which was developed within the commercial finite element package, ABAQUS™—ABAQUS is a trademark of Dassault Systèms; (2) a Python-based results extraction procedure; and (3) a numerical optimization module from the open-source Python library, Scipy. To achieve optimal casting quality, a set of constraints have been defined to ensure directional solidification, and an objective function, based on the solidification cooling rates, has been defined to either maximize, or target a specific, cooling rate. The methodology has been applied to a series of casting and die geometries with different cooling system configurations, including a 2-D axisymmetric wheel and die assembly generated from a full-scale prototype wheel. The results show that, with properly defined constraint and objective functions, solidification conditions can be improved and optimal cooling conditions can be achieved leading to process productivity and product quality improvements.

Comparison of the Delay in Processing Time and Protective Plastic Cases in Two Phosphor Plate Systems

PubMed Central

Aktan, Ali Murat; Çiftçi, Mehmet Ertuğrul; Akgünlü, Faruk

2012-01-01

Objective. The purpose of this study was to analyze two phosphor plate systems (PSPs) (Dürr Dental, Digora Optime) according to their scanning delay and protective plastic case performances. Methods. Two PSPs using an aluminum step wedge were exposed. These plates were placed in three different protective plastic cases (manufacturers' original cases, black case, and white case) before obtaining the radiographs and were then processed immediately and 1, 5, 10, 30, 60, 120, 240, and 480 min after exposure. Mean gray values (MGVs) of the 3rd, 5th, 7th, and 9th steps of the wedges were compared using ANOVA. Results. Statistically significant differences were found between the two PSPs (P < 0.001). ANOVA revealed that the MGVs of four steps of the wedges were significantly different from each other for all scan delays (P < 0.001). MGVs increased with increasing scanning delay, except the group with Dürr plates in their original cases. Reduction in image quality began 5 min after exposure in the other Dürr plate groups. Conclusions. Within the limitations of the current study, it can be concluded that scanning delay causes a reduction in image quality, and using the manufacturer's original protective case will result in better performance of PSPs. PMID:23213301

Comparison of the delay in processing time and protective plastic cases in two phosphor plate systems.

PubMed

Aktan, Ali Murat; Ciftçi, Mehmet Ertuğrul; Akgünlü, Faruk

2012-01-01

The purpose of this study was to analyze two phosphor plate systems (PSPs) (Dürr Dental, Digora Optime) according to their scanning delay and protective plastic case performances. Two PSPs using an aluminum step wedge were exposed. These plates were placed in three different protective plastic cases (manufacturers' original cases, black case, and white case) before obtaining the radiographs and were then processed immediately and 1, 5, 10, 30, 60, 120, 240, and 480 min after exposure. Mean gray values (MGVs) of the 3rd, 5th, 7th, and 9th steps of the wedges were compared using ANOVA. Statistically significant differences were found between the two PSPs (P < 0.001). ANOVA revealed that the MGVs of four steps of the wedges were significantly different from each other for all scan delays (P < 0.001). MGVs increased with increasing scanning delay, except the group with Dürr plates in their original cases. Reduction in image quality began 5 min after exposure in the other Dürr plate groups. Within the limitations of the current study, it can be concluded that scanning delay causes a reduction in image quality, and using the manufacturer's original protective case will result in better performance of PSPs.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

NASA Astrophysics Data System (ADS)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

Practicing chemical process safety: a look at the layers of protection.

PubMed

Sanders, Roy E

2004-11-11

This presentation will review a few public perceptions of safety in chemical plants and refineries, and will compare these plant workplace risks to some of the more traditional occupations. The central theme of this paper is to provide a "within-the-fence" view of many of the process safety practices that world class plants perform to pro-actively protect people, property, profits as well as the environment. It behooves each chemical plant and refinery to have their story on an image-rich presentation to stress stewardship and process safety. Such a program can assure the company's employees and help convince the community that many layers of safety protection within our plants are effective, and protect all from harm.

Ceramic processing: Experimental design and optimization

NASA Technical Reports Server (NTRS)

Weiser, Martin W.; Lauben, David N.; Madrid, Philip

1992-01-01

The objectives of this paper are to: (1) gain insight into the processing of ceramics and how green processing can affect the properties of ceramics; (2) investigate the technique of slip casting; (3) learn how heat treatment and temperature contribute to density, strength, and effects of under and over firing to ceramic properties; (4) experience some of the problems inherent in testing brittle materials and learn about the statistical nature of the strength of ceramics; (5) investigate orthogonal arrays as tools to examine the effect of many experimental parameters using a minimum number of experiments; (6) recognize appropriate uses for clay based ceramics; and (7) measure several different properties important to ceramic use and optimize them for a given application.

Tuning of PID controller using optimization techniques for a MIMO process

NASA Astrophysics Data System (ADS)

Thulasi dharan, S.; Kavyarasan, K.; Bagyaveereswaran, V.

2017-11-01

In this paper, two processes were considered one is Quadruple tank process and the other is CSTR (Continuous Stirred Tank Reactor) process. These are majorly used in many industrial applications for various domains, especially, CSTR in chemical plants.At first mathematical model of both the process is to be done followed by linearization of the system due to MIMO process and controllers are the major part to control the whole process to our desired point as per the applications so the tuning of the controller plays a major role among the whole process. For tuning of parameters we use two optimizations techniques like Particle Swarm Optimization, Genetic Algorithm. The above techniques are majorly used in different applications to obtain which gives the best among all, we use these techniques to obtain the best tuned values among many. Finally, we will compare the performance of the each process with both the techniques.

Dynamic optimization of chemical processes using ant colony framework.

PubMed

Rajesh, J; Gupta, K; Kusumakar, H S; Jayaraman, V K; Kulkarni, B D

2001-11-01

Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples. This new computational tool is simple to implement and can tackle problems with state as well as terminal constraints in a straightforward fashion. It requires fewer grid points to reach the global optimum at relatively very low computational effort. The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.

Optimization Of PVDF-TrFE Processing Conditions For The Fabrication Of Organic MEMS Resonators.

PubMed

Ducrot, Pierre-Henri; Dufour, Isabelle; Ayela, Cédric

2016-01-21

This paper reports a systematic optimization of processing conditions of PVDF-TrFE piezoelectric thin films, used as integrated transducers in organic MEMS resonators. Indeed, despite data on electromechanical properties of PVDF found in the literature, optimized processing conditions that lead to these properties remain only partially described. In this work, a rigorous optimization of parameters enabling state-of-the-art piezoelectric properties of PVDF-TrFE thin films has been performed via the evaluation of the actuation performance of MEMS resonators. Conditions such as annealing duration, poling field and poling duration have been optimized and repeatability of the process has been demonstrated.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

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.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian

Resist process optimization for further defect reduction

NASA Astrophysics Data System (ADS)

Tanaka, Keiichi; Iseki, Tomohiro; Marumoto, Hiroshi; Takayanagi, Koji; Yoshida, Yuichi; Uemura, Ryouichi; Yoshihara, Kosuke

2012-03-01

Defect reduction has become one of the most important technical challenges in device mass-production. Knowing that resist processing on a clean track strongly impacts defect formation in many cases, we have been trying to improve the track process to enhance customer yield. For example, residual type defect and pattern collapse are strongly related to process parameters in developer, and we have reported new develop and rinse methods in the previous papers. Also, we have reported the optimization method of filtration condition to reduce bridge type defects, which are mainly caused by foreign substances such as gels in resist. Even though we have contributed resist caused defect reduction in past studies, defect reduction requirements continue to be very important. In this paper, we will introduce further process improvements in terms of resist defect reduction, including the latest experimental data.

Optimal design of the satellite constellation arrangement reconfiguration process

NASA Astrophysics Data System (ADS)

Fakoor, Mahdi; Bakhtiari, Majid; Soleymani, Mahshid

2016-08-01

In this article, a novel approach is introduced for the satellite constellation reconfiguration based on Lambert's theorem. Some critical problems are raised in reconfiguration phase, such as overall fuel cost minimization, collision avoidance between the satellites on the final orbital pattern, and necessary maneuvers for the satellites in order to be deployed in the desired position on the target constellation. To implement the reconfiguration phase of the satellite constellation arrangement at minimal cost, the hybrid Invasive Weed Optimization/Particle Swarm Optimization (IWO/PSO) algorithm is used to design sub-optimal transfer orbits for the satellites existing in the constellation. Also, the dynamic model of the problem will be modeled in such a way that, optimal assignment of the satellites to the initial and target orbits and optimal orbital transfer are combined in one step. Finally, we claim that our presented idea i.e. coupled non-simultaneous flight of satellites from the initial orbital pattern will lead to minimal cost. The obtained results show that by employing the presented method, the cost of reconfiguration process is reduced obviously.

Optimization Of PVDF-TrFE Processing Conditions For The Fabrication Of Organic MEMS Resonators

PubMed Central

Ducrot, Pierre-Henri; Dufour, Isabelle; Ayela, Cédric

2016-01-01

This paper reports a systematic optimization of processing conditions of PVDF-TrFE piezoelectric thin films, used as integrated transducers in organic MEMS resonators. Indeed, despite data on electromechanical properties of PVDF found in the literature, optimized processing conditions that lead to these properties remain only partially described. In this work, a rigorous optimization of parameters enabling state-of-the-art piezoelectric properties of PVDF-TrFE thin films has been performed via the evaluation of the actuation performance of MEMS resonators. Conditions such as annealing duration, poling field and poling duration have been optimized and repeatability of the process has been demonstrated. PMID:26792224

Numerical simulation and optimization of casting process for complex pump

NASA Astrophysics Data System (ADS)

Liu, Xueqin; Dong, Anping; Wang, Donghong; Lu, Yanling; Zhu, Guoliang

2017-09-01

The complex shape of the casting pump body has large complicated structure and uniform wall thickness, which easy give rise to casting defects. The numerical simulation software ProCAST is used to simulate the initial top gating process, after analysis of the material and structure characteristics of the high-pressure pump. The filling process was overall smooth, not there the water shortage phenomenon. But the circular shrinkage defects appear at the bottom of casting during solidification process. Then, the casting parameters were optimized and adding cold iron in the bottom. The shrinkage weight was reduced from 0.00167g to 0.0005g. The porosity volume was reduced from 1.39cm3 to 0.41cm3. The optimization scheme is simulated and actual experimented. The defect has been significantly improved.

Co-optimization of lithographic and patterning processes for improved EPE performance

NASA Astrophysics Data System (ADS)

Maslow, Mark J.; Timoshkov, Vadim; Kiers, Ton; Jee, Tae Kwon; de Loijer, Peter; Morikita, Shinya; Demand, Marc; Metz, Andrew W.; Okada, Soichiro; Kumar, Kaushik A.; Biesemans, Serge; Yaegashi, Hidetami; Di Lorenzo, Paolo; Bekaert, Joost P.; Mao, Ming; Beral, Christophe; Larivière, Stephane

2017-03-01

Complimentary lithography is already being used for advanced logic patterns. The tight pitches for 1D Metal layers are expected to be created using spacer based multiple patterning ArF-i exposures and the more complex cut/block patterns are made using EUV exposures. At the same time, control requirements of CDU, pattern shift and pitch-walk are approaching sub-nanometer levels to meet edge placement error (EPE) requirements. Local variability, such as Line Edge Roughness (LER), Local CDU, and Local Placement Error (LPE), are dominant factors in the total Edge Placement error budget. In the lithography process, improving the imaging contrast when printing the core pattern has been shown to improve the local variability. In the etch process, it has been shown that the fusion of atomic level etching and deposition can also improve these local variations. Co-optimization of lithography and etch processing is expected to further improve the performance over individual optimizations alone. To meet the scaling requirements and keep process complexity to a minimum, EUV is increasingly seen as the platform for delivering the exposures for both the grating and the cut/block patterns beyond N7. In this work, we evaluated the overlay and pattern fidelity of an EUV block printed in a negative tone resist on an ArF-i SAQP grating. High-order Overlay modeling and corrections during the exposure can reduce overlay error after development, a significant component of the total EPE. During etch, additional degrees of freedom are available to improve the pattern placement error in single layer processes. Process control of advanced pitch nanoscale-multi-patterning techniques as described above is exceedingly complicated in a high volume manufacturing environment. Incorporating potential patterning optimizations into both design and HVM controls for the lithography process is expected to bring a combined benefit over individual optimizations. In this work we will show the EPE

PLUTONIUM PROCESSING OPTIMIZATION IN SUPPORT OF THE MOX FUEL PROGRAM

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

GRAY, DEVIN W.; COSTA, DAVID A.

2007-02-02

After Los Alamos National Laboratory (LANL) personnel completed polishing 125 Kg of plutonium as highly purified PuO{sub 2} from surplus nuclear weapons, Duke, COGEMA, Stone, and Webster (DCS) required as the next process stage, the validation and optimization of all phases of the plutonium polishing flow sheet. Personnel will develop the optimized parameters for use in the upcoming 330 kg production mission.

Robust resolution enhancement optimization methods to process variations based on vector imaging model

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong

2012-03-01

Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.

Process for the preparation of protected dihydroxypropyl trialkylammonium salts and derivatives thereof

DOEpatents

Hollingsworth, Rawle I.; Wang, Guijun

2000-01-01

A process for the preparation of protected dihydroxypropyl trialkylammonium salts, particularly in chiral form is described. In particular, a process for the preparation of (2,2-dimethyl-1,3-dioxolan-4-ylmethyl)trialkylammonium salts, particularly in chiral form is described. Furthermore, a process is described wherein the (2,2-dimethyl-1,3-dioxolan-4ylmethyl)trialkylammonium salts is a 2,2-dimethyl-1,3-dioxolan-4-ylmethyl trimethylammonium salt, preferably in chiral form. The protected dihydroxypropyl trialkylammonium salts lead to L-carnitine (9) when in chiral form (5).

Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

NASA Astrophysics Data System (ADS)

Ozkat, Erkan Caner; Franciosa, Pasquale; Ceglarek, Dariusz

2017-08-01

Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 °C) and the vapourizing temperature of the zinc (∼907 °C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple-inputs (i.e. key control characteristics) and multiple-outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp-Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii

Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

PubMed Central

Parida, Arun Kumar; Routara, Bharat Chandra

2014-01-01

Taguchi's design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (R a). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v 3-f 2-d 3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v 1-f 1-d 3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach. PMID:27437503

Optimization of composite wood structural components : processing and design choices

Treesearch

Theodore L. Laufenberg

1985-01-01

Decreasing size and quality of the world's forest resources are responsible for interest in producing composite wood structural components. Process and design optimization methods are offered in this paper. Processing concepts for wood composite structural products are reviewed to illustrate manufacturing boundaries and areas of high potential. Structural...

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

NASA Astrophysics Data System (ADS)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Speedup for quantum optimal control from automatic differentiation based on graphics processing units

NASA Astrophysics Data System (ADS)

Leung, Nelson; Abdelhafez, Mohamed; Koch, Jens; Schuster, David

2017-04-01

We implement a quantum optimal control algorithm based on automatic differentiation and harness the acceleration afforded by graphics processing units (GPUs). Automatic differentiation allows us to specify advanced optimization criteria and incorporate them in the optimization process with ease. We show that the use of GPUs can speedup calculations by more than an order of magnitude. Our strategy facilitates efficient numerical simulations on affordable desktop computers and exploration of a host of optimization constraints and system parameters relevant to real-life experiments. We demonstrate optimization of quantum evolution based on fine-grained evaluation of performance at each intermediate time step, thus enabling more intricate control on the evolution path, suppression of departures from the truncated model subspace, as well as minimization of the physical time needed to perform high-fidelity state preparation and unitary gates.

Equal Protection and Due Process: Contrasting Methods of Review under Fourteenth Amendment Doctrine.

ERIC Educational Resources Information Center

Hughes, James A.

1979-01-01

Argues that the Court has, at times, confused equal protection and due process methods of review, primarily by employing interest balancing in certain equal protection cases that should have been subjected to due process analysis. Available from Harvard Civil Rights-Civil Liberties Law Review, Harvard Law School, Cambridge, MA 02138; sc $4.00.…

Process optimization for osmo-dehydrated carambola (Averrhoa carambola L) slices and its storage studies.

PubMed

Roopa, N; Chauhan, O P; Raju, P S; Das Gupta, D K; Singh, R K R; Bawa, A S

2014-10-01

An osmotic-dehydration process protocol for Carambola (Averrhoacarambola L.,), an exotic star shaped tropical fruit, was developed. The process was optimized using Response Surface Methodology (RSM) following Central Composite Rotatable Design (CCRD). The experimental variables selected for the optimization were soak solution concentration (°Brix), soaking temperature (°C) and soaking time (min) with 6 experiments at central point. The effect of process variables was studied on solid gain and water loss during osmotic dehydration process. The data obtained were analyzed employing multiple regression technique to generate suitable mathematical models. Quadratic models were found to fit well (R(2), 95.58 - 98.64 %) in describing the effect of variables on the responses studied. The optimized levels of the process variables were achieved at 70°Brix, 48 °C and 144 min for soak solution concentration, soaking temperature and soaking time, respectively. The predicted and experimental results at optimized levels of variables showed high correlation. The osmo-dehydrated product prepared at optimized conditions showed a shelf-life of 10, 8 and 6 months at 5 °C, ambient (30 ± 2 °C) and 37 °C, respectively.

Mechanoluminescence assisting agile optimization of processing design on surgical epiphysis plates

NASA Astrophysics Data System (ADS)

Terasaki, Nao; Toyomasu, Takashi; Sonohata, Motoki

2018-04-01

We propose a novel method for agile optimization of processing design by visualization of mechanoluminescence. To demonstrate the effect of the new method, epiphysis plates were processed to form dots (diameters: 1 and 1.5 mm) and the mechanical information was evaluated. As a result, the appearance of new strain concentration was successfully visualized on the basis of mechanoluminescence, and complex mechanical information was instinctively understood by surgeons as the designers. In addition, it was clarified by mechanoluminescence analysis that small dots do not have serious mechanical effects such as strength reduction. Such detail mechanical information evaluated on the basis of mechanoluminescence was successfully applied to the judgement of the validity of the processing design. This clearly proves the effectiveness of the new methodology using mechanoluminescence for assisting agile optimization of the processing design.

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

A neural network strategy for end-point optimization of batch processes.

PubMed

Krothapally, M; Palanki, S

1999-01-01

The traditional way of operating batch processes has been to utilize an open-loop "golden recipe". However, there can be substantial batch to batch variation in process conditions and this open-loop strategy can lead to non-optimal operation. In this paper, a new approach is presented for end-point optimization of batch processes by utilizing neural networks. This strategy involves the training of two neural networks; one to predict switching times and the other to predict the input profile in the singular region. This approach alleviates the computational problems associated with the classical Pontryagin's approach and the nonlinear programming approach. The efficacy of this scheme is illustrated via simulation of a fed-batch fermentation.

Optimization of cutting parameters for machining time in turning process

NASA Astrophysics Data System (ADS)

Mavliutov, A. R.; Zlotnikov, E. G.

2018-03-01

This paper describes the most effective methods for nonlinear constraint optimization of cutting parameters in the turning process. Among them are Linearization Programming Method with Dual-Simplex algorithm, Interior Point method, and Augmented Lagrangian Genetic Algorithm (ALGA). Every each of them is tested on an actual example – the minimization of production rate in turning process. The computation was conducted in the MATLAB environment. The comparative results obtained from the application of these methods show: The optimal value of the linearized objective and the original function are the same. ALGA gives sufficiently accurate values, however, when the algorithm uses the Hybrid function with Interior Point algorithm, the resulted values have the maximal accuracy.

Co-Simulation for Advanced Process Design and Optimization

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

Stephen E. Zitney

2009-01-01

Meeting the increasing demand for clean, affordable, and secure energy is arguably the most important challenge facing the world today. Fossil fuels can play a central role in a portfolio of carbon-neutral energy options provided CO{sub 2} emissions can be dramatically reduced by capturing CO{sub 2} and storing it safely and effectively. Fossil energy industry faces the challenge of meeting aggressive design goals for next-generation power plants with CCS. Process designs will involve large, highly-integrated, and multipurpose systems with advanced equipment items with complex geometries and multiphysics. APECS is enabling software to facilitate effective integration, solution, and analysis of high-fidelitymore » process/equipment (CFD) co-simulations. APECS helps to optimize fluid flow and related phenomena that impact overall power plant performance. APECS offers many advanced capabilities including ROMs, design optimization, parallel execution, stochastic analysis, and virtual plant co-simulations. NETL and its collaborative R&D partners are using APECS to reduce the time, cost, and technical risk of developing high-efficiency, zero-emission power plants with CCS.« less

Information theoretic methods for image processing algorithm optimization

NASA Astrophysics Data System (ADS)

Prokushkin, Sergey F.; Galil, Erez

2015-01-01

Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

Process Parameters Optimization in Single Point Incremental Forming

NASA Astrophysics Data System (ADS)

Gulati, Vishal; Aryal, Ashmin; Katyal, Puneet; Goswami, Amitesh

2016-04-01

This work aims to optimize the formability and surface roughness of parts formed by the single-point incremental forming process for an Aluminium-6063 alloy. The tests are based on Taguchi's L18 orthogonal array selected on the basis of DOF. The tests have been carried out on vertical machining center (DMC70V); using CAD/CAM software (SolidWorks V5/MasterCAM). Two levels of tool radius, three levels of sheet thickness, step size, tool rotational speed, feed rate and lubrication have been considered as the input process parameters. Wall angle and surface roughness have been considered process responses. The influential process parameters for the formability and surface roughness have been identified with the help of statistical tool (response table, main effect plot and ANOVA). The parameter that has the utmost influence on formability and surface roughness is lubrication. In the case of formability, lubrication followed by the tool rotational speed, feed rate, sheet thickness, step size and tool radius have the influence in descending order. Whereas in surface roughness, lubrication followed by feed rate, step size, tool radius, sheet thickness and tool rotational speed have the influence in descending order. The predicted optimal values for the wall angle and surface roughness are found to be 88.29° and 1.03225 µm. The confirmation experiments were conducted thrice and the value of wall angle and surface roughness were found to be 85.76° and 1.15 µm respectively.

Optimization of injection molding process parameters for a plastic cell phone housing component

NASA Astrophysics Data System (ADS)

Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

2016-11-01

To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

Verifying and Validating Proposed Models for FSW Process Optimization

NASA Technical Reports Server (NTRS)

Schneider, Judith

2008-01-01

This slide presentation reviews Friction Stir Welding (FSW) and the attempts to model the process in order to optimize and improve the process. The studies are ongoing to validate and refine the model of metal flow in the FSW process. There are slides showing the conventional FSW process, a couple of weld tool designs and how the design interacts with the metal flow path. The two basic components of the weld tool are shown, along with geometries of the shoulder design. Modeling of the FSW process is reviewed. Other topics include (1) Microstructure features, (2) Flow Streamlines, (3) Steady-state Nature, and (4) Grain Refinement Mechanisms

Process and Energy Optimization Assessment, Tobyhanna Army Depot, PA

DTIC Science & Technology

2006-04-17

assembly of electronic-communication components, different welding processes are performed at TYAD. It uses shielded arc, metal inert gas (MIG...tungsten inert gas ( TIG ), and silver braz- ing oxygen/acetylene cutting plasma arc methods to complete mission re- quirements. Major welding jobs are...ER D C/ CE R L TR -0 6 -1 1 Process and Energy Optimization Assessment Tobyhanna Army Depot, PA Mike C.J. Lin, Alexander M. Zhivov

Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

NASA Astrophysics Data System (ADS)

Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

2010-12-01

Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.

Process-time Optimization of Vacuum Degassing Using a Genetic Alloy Design Approach

PubMed Central

Dilner, David; Lu, Qi; Mao, Huahai; Xu, Wei; van der Zwaag, Sybrand; Selleby, Malin

2014-01-01

This paper demonstrates the use of a new model consisting of a genetic algorithm in combination with thermodynamic calculations and analytical process models to minimize the processing time during a vacuum degassing treatment of liquid steel. The model sets multiple simultaneous targets for final S, N, O, Si and Al levels and uses the total slag mass, the slag composition, the steel composition and the start temperature as optimization variables. The predicted optimal conditions agree well with industrial practice. For those conditions leading to the shortest process time the target compositions for S, N and O are reached almost simultaneously. PMID:28788286

OPTIMIZATION OF COUNTERCURRENT STAGED PROCESSES.

DTIC Science & Technology

CHEMICAL ENGINEERING , OPTIMIZATION), (*DISTILLATION, OPTIMIZATION), INDUSTRIAL PRODUCTION, INDUSTRIAL EQUIPMENT, MATHEMATICAL MODELS, DIFFERENCE EQUATIONS, NONLINEAR PROGRAMMING, BOUNDARY VALUE PROBLEMS, NUMERICAL INTEGRATION

Mechanism of cross-sectoral coordination between nature protection and forestry in the Natura 2000 formulation process in Slovakia.

PubMed

Sarvašová, Zuzana; Sálka, Jaroslav; Dobšinská, Zuzana

2013-09-01

Nature protection as a policy sector is not isolated and is directly or indirectly influenced by many other sectors (e.g. forestry, water management, rural development, energy, etc.). These policy sectors are neither completely segmented nor unaffected by the decisions taken in other policy sectors. Policy formulation in nature protection is therefore also influenced by different sectors. For that reason it is inevitable to stress the need for inter-sectoral coordination to assure their policy coherence. The aim of this article is to describe the mechanism and modes of cross-sectoral coordination and to analyze the relevant actors and their interaction, using the case of the Natura 2000 formulation process in Slovakia. The European Union (EU) set up an ecological network of special protected areas, known as Natura 2000 to ensure biodiversity by conserving natural habitats and wild fauna and flora in the territory of the Member States. An optimized nature protection must therefore carefully consider existing limits and crossdisciplinary relationships at the EU, national and regional levels. The relations between forestry and biodiversity protection are analyzed using the advocacy coalition framework (ACF). The ACF is used for analyzing how two coalitions, in this case ecological and forest owners' coalitions, advocate or pursue their beliefs from the nature protection and forestry policy field. The whole process is illustrated at the regional scale on the case study of Natura 2000 sites formulation in the Slovak Republic. For better reliability and validity of research, a combination of various empiric research methods was used, supported by existing theories. So called triangulation of sociological research or triangulation of methods consists of mutual results testing of individual methodological steps through identifying corresponding political-science theories, assessing their formal points using primary and secondary document analysis and assessing their

Optimization of the coherence function estimation for multi-core central processing unit

NASA Astrophysics Data System (ADS)

Cheremnov, A. G.; Faerman, V. A.; Avramchuk, V. S.

2017-02-01

The paper considers use of parallel processing on multi-core central processing unit for optimization of the coherence function evaluation arising in digital signal processing. Coherence function along with other methods of spectral analysis is commonly used for vibration diagnosis of rotating machinery and its particular nodes. An algorithm is given for the function evaluation for signals represented with digital samples. The algorithm is analyzed for its software implementation and computational problems. Optimization measures are described, including algorithmic, architecture and compiler optimization, their results are assessed for multi-core processors from different manufacturers. Thus, speeding-up of the parallel execution with respect to sequential execution was studied and results are presented for Intel Core i7-4720HQ и AMD FX-9590 processors. The results show comparatively high efficiency of the optimization measures taken. In particular, acceleration indicators and average CPU utilization have been significantly improved, showing high degree of parallelism of the constructed calculating functions. The developed software underwent state registration and will be used as a part of a software and hardware solution for rotating machinery fault diagnosis and pipeline leak location with acoustic correlation method.

28nm node process optimization: a lithography centric view

NASA Astrophysics Data System (ADS)

Seltmann, Rolf

2014-10-01

Many experts claim that the 28nm technology node will be the most cost effective technology node forever. This results from primarily from the cost of manufacturing due to the fact that 28nm is the last true Single Patterning (SP) node. It is also affected by the dramatic increase of design costs and the limited shrink factor of the next following nodes. Thus, it is assumed that this technology still will be alive still for many years. To be cost competitive, high yields are mandatory. Meanwhile, leading edge foundries have optimized the yield of the 28nm node to such a level that that it is nearly exclusively defined by random defectivity. However, it was a long way to go to come to that level. In my talk I will concentrate on the contribution of lithography to this yield learning curve. I will choose a critical metal patterning application. I will show what was needed to optimize the process window to a level beyond the usual OPC model work that was common on previous nodes. Reducing the process (in particular focus) variability is a complementary need. It will be shown which improvements were needed in tooling, process control and design-mask-wafer interaction to remove all systematic yield detractors. Over the last couple of years new scanner platforms were introduced that were targeted for both better productivity and better parametric performance. But this was not a clear run-path. It needed some extra affords of the tool suppliers together with the Fab to bring the tool variability down to the necessary level. Another important topic to reduce variability is the interaction of wafer none-planarity and lithography optimization. Having an accurate knowledge of within die topography is essential for optimum patterning. By completing both the variability reduction work and the process window enhancement work we were able to transfer the original marginal process budget to a robust positive budget and thus ensuring high yield and low costs.

COLA: Optimizing Stream Processing Applications via Graph Partitioning

NASA Astrophysics Data System (ADS)

Khandekar, Rohit; Hildrum, Kirsten; Parekh, Sujay; Rajan, Deepak; Wolf, Joel; Wu, Kun-Lung; Andrade, Henrique; Gedik, Buğra

In this paper, we describe an optimization scheme for fusing compile-time operators into reasonably-sized run-time software units called processing elements (PEs). Such PEs are the basic deployable units in System S, a highly scalable distributed stream processing middleware system. Finding a high quality fusion significantly benefits the performance of streaming jobs. In order to maximize throughput, our solution approach attempts to minimize the processing cost associated with inter-PE stream traffic while simultaneously balancing load across the processing hosts. Our algorithm computes a hierarchical partitioning of the operator graph based on a minimum-ratio cut subroutine. We also incorporate several fusion constraints in order to support real-world System S jobs. We experimentally compare our algorithm with several other reasonable alternative schemes, highlighting the effectiveness of our approach.

Optimal Conservation Outcomes Require Both Restoration and Protection

PubMed Central

Possingham, Hugh P.; Bode, Michael; Klein, Carissa J.

2015-01-01

Conservation outcomes are principally achieved through the protection of intact habitat or the restoration of degraded habitat. Restoration is generally considered a lower priority action than protection because protection is thought to provide superior outcomes, at lower costs, without the time delay required for restoration. Yet while it is broadly accepted that protected intact habitat safeguards more biodiversity and generates greater ecosystem services per unit area than restored habitat, conservation lacks a theory that can coherently compare the relative outcomes of the two actions. We use a dynamic landscape model to integrate these two actions into a unified conservation theory of protection and restoration. Using nonlinear benefit functions, we show that both actions are crucial components of a conservation strategy that seeks to optimise either biodiversity conservation or ecosystem services provision. In contrast to conservation orthodoxy, in some circumstances, restoration should be strongly preferred to protection. The relative priority of protection and restoration depends on their costs and also on the different time lags that are inherent to both protection and restoration. We derive a simple and easy-to-interpret heuristic that integrates these factors into a single equation that applies equally to biodiversity conservation and ecosystem service objectives. We use two examples to illustrate the theory: bird conservation in tropical rainforests and coastal defence provided by mangrove forests. PMID:25625277

Optimal conservation outcomes require both restoration and protection.

PubMed

Possingham, Hugh P; Bode, Michael; Klein, Carissa J

2015-01-01

Conservation outcomes are principally achieved through the protection of intact habitat or the restoration of degraded habitat. Restoration is generally considered a lower priority action than protection because protection is thought to provide superior outcomes, at lower costs, without the time delay required for restoration. Yet while it is broadly accepted that protected intact habitat safeguards more biodiversity and generates greater ecosystem services per unit area than restored habitat, conservation lacks a theory that can coherently compare the relative outcomes of the two actions. We use a dynamic landscape model to integrate these two actions into a unified conservation theory of protection and restoration. Using nonlinear benefit functions, we show that both actions are crucial components of a conservation strategy that seeks to optimise either biodiversity conservation or ecosystem services provision. In contrast to conservation orthodoxy, in some circumstances, restoration should be strongly preferred to protection. The relative priority of protection and restoration depends on their costs and also on the different time lags that are inherent to both protection and restoration. We derive a simple and easy-to-interpret heuristic that integrates these factors into a single equation that applies equally to biodiversity conservation and ecosystem service objectives. We use two examples to illustrate the theory: bird conservation in tropical rainforests and coastal defence provided by mangrove forests.

Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates.

PubMed

Kaplan, Jonas T; Gimbel, Sarah I; Dehghani, Morteza; Immordino-Yang, Mary Helen; Sagae, Kenji; Wong, Jennifer D; Tipper, Christine M; Damasio, Hanna; Gordon, Andrew S; Damasio, Antonio

2017-02-01

Narratives are an important component of culture and play a central role in transmitting social values. Little is known, however, about how the brain of a listener/reader processes narratives. A receiver's response to narration is influenced by the narrator's framing and appeal to values. Narratives that appeal to "protected values," including core personal, national, or religious values, may be particularly effective at influencing receivers. Protected values resist compromise and are tied with identity, affective value, moral decision-making, and other aspects of social cognition. Here, we investigated the neural mechanisms underlying reactions to protected values in narratives. During fMRI scanning, we presented 78 American, Chinese, and Iranian participants with real-life stories distilled from a corpus of over 20 million weblogs. Reading these stories engaged the posterior medial, medial prefrontal, and temporo-parietal cortices. When participants believed that the protagonist was appealing to a protected value, signal in these regions was increased compared with when no protected value was perceived, possibly reflecting the intensive and iterative search required to process this material. The effect strength also varied across groups, potentially reflecting cultural differences in the degree of concern for protected values. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Optimal nonlinear information processing capacity in delay-based reservoir computers

NASA Astrophysics Data System (ADS)

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-09-01

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

Optimal nonlinear information processing capacity in delay-based reservoir computers

PubMed Central

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-01-01

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature. PMID:26358528

Optimal nonlinear information processing capacity in delay-based reservoir computers.

PubMed

Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

2015-09-11

Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature.

Analysis and optimization of coagulation and flocculation process

NASA Astrophysics Data System (ADS)

Saritha, V.; Srinivas, N.; Srikanth Vuppala, N. V.

2017-03-01

Natural coagulants have been the focus of research of many investigators through the last decade owing to the problems caused by the chemical coagulants. Optimization of process parameters is vital for the effectiveness of coagulation process. In the present study optimization of parameters like pH, dose of coagulant and mixing speed were studied using natural coagulants sago and chitin in comparison with alum. Jar test apparatus was used to perform the coagulation. The results showed that the removal of turbidity was up to 99 % by both alum and chitin at lower doses of coagulant, i.e., 0.1-0.3 g/L, whereas sago has shown a reduction of 70-100 % at doses of 0.1 and 0.2 g/L. The optimum conditions observed for sago were 6 and 7 whereas chitin was stable at all pH ranges, lower coagulant doses, i.e., 0.1-0.3 g/L and mixing speed—rapid mixing at 100 rpm for 10 min and slow mixing 20 rpm for 20 min. Hence, it can be concluded that sago and chitin can be used for treating water even with large seasonal variation in turbidity.

Media milling process optimization for manufacture of drug nanoparticles using design of experiments (DOE).

PubMed

Nekkanti, Vijaykumar; Marwah, Ashwani; Pillai, Raviraj

2015-01-01

Design of experiments (DOE), a component of Quality by Design (QbD), is systematic and simultaneous evaluation of process variables to develop a product with predetermined quality attributes. This article presents a case study to understand the effects of process variables in a bead milling process used for manufacture of drug nanoparticles. Experiments were designed and results were computed according to a 3-factor, 3-level face-centered central composite design (CCD). The factors investigated were motor speed, pump speed and bead volume. Responses analyzed for evaluating these effects and interactions were milling time, particle size and process yield. Process validation batches were executed using the optimum process conditions obtained from software Design-Expert® to evaluate both the repeatability and reproducibility of bead milling technique. Milling time was optimized to <5 h to obtain the desired particle size (d90 < 400 nm). The desirability function used to optimize the response variables and observed responses were in agreement with experimental values. These results demonstrated the reliability of selected model for manufacture of drug nanoparticles with predictable quality attributes. The optimization of bead milling process variables by applying DOE resulted in considerable decrease in milling time to achieve the desired particle size. The study indicates the applicability of DOE approach to optimize critical process parameters in the manufacture of drug nanoparticles.

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

Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production.

PubMed

Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens

2009-11-01

In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.

Understanding processes of risk and protection that shape the sexual and reproductive health of young women affected by conflict: the price of protection.

PubMed

Hutchinson, Aisha; Waterhouse, Philippa; March-McDonald, Jane; Neal, Sarah; Ingham, Roger

2017-01-01

It is assumed that knowing what puts young women at risk of poor sexual health outcomes and, in turn, what protects them against these outcomes, will enable greater targeted protection as well as help in designing more effective programmes. Accordingly, efforts have been directed towards mapping risk and protective factors onto general ecological frameworks, but these currently do not take into account the context of modern armed conflict. A literature overview approach was used to identify SRH related risk and protective factors specifically for young women affected by modern armed conflict. A range of keywords were used to identify academic articles which explored the sexual and reproductive health needs of young women affected by modern armed conflict. Selected articles were read to identify risk and protective factors in relation to sexual and reproductive health. While no articles explicitly identified 'risk' or 'protective' factors, we were able to extrapolate these through a thorough engagement with the text. However, we found that it was difficult to identify factors as either 'risky' or 'protective', with many having the capacity to be both risky and protective (i.e. refugee camps or family). Therefore, using an ecological model, six environments that impact upon young women's lives in contexts of modern armed conflict are used to illustrate the dynamic and complex operation of risk and protection - highlighting processes of protection and the 'trade-offs' between risks. We conclude that there are no simple formulaic risk/protection patterns to be applied in every conflict and post-conflict context. Instead, there needs to be greater recognition of the 'processes' of protection, including the role of 'trade-offs' (what we term as 'protection at a price'), in order to further effective policy and practical responses to improve sexual and reproductive health outcomes during or following armed conflict. Focus on specific 'factors' (such as 'female headed

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

Optimization of intracerebral tumour protection by active-specific immunization against murine melanoma B16/G3.12.

PubMed

Staib, L; Harel, W; Mitchell, M S

2001-08-01

Development of brain metastases despite extracerebral response to systemic immunotherapy is a common problem in melanoma patients. We have previously described a murine melanoma vaccine of interferon-gamma (IFNgamma)-treated, irradiated syngeneic B16/G3.12 and allogeneic (Cloudman) melanoma cells, plus the adjuvant DETOX, that is protective against subcutaneous (93%) or intracerebral (69%) syngeneic challenge. This study aimed to optimize this vaccine. Groups of nine or 10 mice were immunized five times in 5 weeks with: (i) complete vaccine +/- IFNgamma (VAC+, VAC-); (ii) syngeneic 2 x 106 G3.12 cells plus DETOX (Syn+D), (iii) 2 x 106 allogeneic Cloudman cells plus DETOX (Allo+D); (iv) VAC+ without DETOX (no DETOX); (v) DETOX alone (DETOX); or (vi) phosphate buffered saline (PBS). Mice were challenged subcutaneously with 104 viable G3.12 (or Cloudman cells) and after 35 days intracerebrally with 104 G3.12 cells. Expression of H-2 antigens (measured using fluorescence-activated cell sorting), splenocyte cytotoxicity (measured using 51Cr release) and median overall survival (OAS) were analysed using the log-rank test. VAC+, VAC- and G3.12 mice were equally protected from subcutaneous (s.c.) and intracerebral (i.c.) melanoma challenge (OAS 65 days for s.c., 30 days for i.c.). Protection was less (P < 0.05) in DETOX mice (48 days for s.c.), PBS mice (47 days for s.c., 21 days for i.c.) or no DETOX mice (51 days for s.c.). Allo+D mice showed s.c. (59 days) but not i.c. protection (20 days). IFNgamma incubation did not increase the effect in either the challenge cells or the vaccine cells (P > 0.05). Specific cytotoxicity was seen with G3.12 targets in VAC+ (27%) but not PBS (2%; P < 0.05) mice with equal NK (YAC-1) lysis (10% versus 7%; P< 0.05). Optimal protection against s.c./i.c. experimental murine melanoma was yielded by irradiated syngeneic cells plus DETOX. DETOX alone was not active. Upregulation of H-2 antigens with IFNgamma under these conditions does not

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.

[Study on the optimal extraction process of chaihushugan powder].

PubMed

Wang, Chun-yan; Zhang, Wan-ming; Zhang, Dan-shen; An, Fang; Tian, Jia-ming

2009-11-01

To study the optimal extraction process of chaihushugan powder by orthogonal design. RP-HPLC method was developed for the determination of saikosaponin a, ferulic acid, hesperidin and paeoniflorin in chaihushugan powder. The contents of the components and the extraction yield were selected as assessment indices. Four factors were study by L9 (3(4)), including the alcohol concentration, amount of alcohol, duration of extraction and times of extraction. The optimal extracting condition was 80% alcohol consumed as 10 times of crude herb amount, and extracting two times for 90 min each time. This study supplies theoretical base for the development of chaihushugan powder formulation.

Optimization of Tape Winding Process Parameters to Enhance the Performance of Solid Rocket Nozzle Throat Back Up Liners using Taguchi's Robust Design Methodology

NASA Astrophysics Data System (ADS)

Nath, Nayani Kishore

2017-08-01

The throat back up liners is used to protect the nozzle structural members from the severe thermal environment in solid rocket nozzles. The throat back up liners is made with E-glass phenolic prepregs by tape winding process. The objective of this work is to demonstrate the optimization of process parameters of tape winding process to achieve better insulative resistance using Taguchi's robust design methodology. In this method four control factors machine speed, roller pressure, tape tension, tape temperature that were investigated for the tape winding process. The presented work was to study the cogency and acceptability of Taguchi's methodology in manufacturing of throat back up liners. The quality characteristic identified was Back wall temperature. Experiments carried out using L 9 ' (34) orthogonal array with three levels of four different control factors. The test results were analyzed using smaller the better criteria for Signal to Noise ratio in order to optimize the process. The experimental results were analyzed conformed and successfully used to achieve the minimum back wall temperature of the throat back up liners. The enhancement in performance of the throat back up liners was observed by carrying out the oxy-acetylene tests. The influence of back wall temperature on the performance of throat back up liners was verified by ground firing test.

Multi objective optimization model for minimizing production cost and environmental impact in CNC turning process

NASA Astrophysics Data System (ADS)

Widhiarso, Wahyu; Rosyidi, Cucuk Nur

2018-02-01

Minimizing production cost in a manufacturing company will increase the profit of the company. The cutting parameters will affect total processing time which then will affect the production cost of machining process. Besides affecting the production cost and processing time, the cutting parameters will also affect the environment. An optimization model is needed to determine the optimum cutting parameters. In this paper, we develop an optimization model to minimize the production cost and the environmental impact in CNC turning process. The model is used a multi objective optimization. Cutting speed and feed rate are served as the decision variables. Constraints considered are cutting speed, feed rate, cutting force, output power, and surface roughness. The environmental impact is converted from the environmental burden by using eco-indicator 99. Numerical example is given to show the implementation of the model and solved using OptQuest of Oracle Crystal Ball software. The results of optimization indicate that the model can be used to optimize the cutting parameters to minimize the production cost and the environmental impact.

[Optimization of processing technology for semen cuscuta by uniform and regression analysis].

PubMed

Li, Chun-yu; Luo, Hui-yu; Wang, Shu; Zhai, Ya-nan; Tian, Shu-hui; Zhang, Dan-shen

2011-02-01

To optimize the best preparation technology for the contains of total flavornoids, polysaccharides, the percentage of water and alcohol-soluble components in Semen Cuscuta herb processing. UV-spectrophotometry was applied to determine the contains of total flavornoids and polysaccharides, which were extracted from Semen Cuscuta. And the processing was optimized by the way of uniform design and contour map. The best preparation technology was satisfied with some conditions as follows: baking temperature 150 degrees C, baking time 140 seconds. The regression models are notable and reasonable, which can forecast results precisely.

Hydroxyapatite coatings for marble protection: Optimization of calcite covering and acid resistance

NASA Astrophysics Data System (ADS)

Graziani, Gabriela; Sassoni, Enrico; Franzoni, Elisa; Scherer, George W.

2016-04-01

Hydroxyapatite (HAP) has a much lower dissolution rate and solubility than calcite, especially in an acidic environment, so it has been proposed for the protection of marble against acidic rain corrosion. Promising results were obtained, but further optimization is necessary as the treated layer is often incomplete, cracked and/or porous. In this paper, several parameters were investigated to obtain a coherent, uncracked layer, and to avoid the formation of metastable, soluble phases instead of HAP: the role of the pH of the starting solution; the effect of organic and inorganic additions, and in particular that of ethanol, as it is reported to adsorb on calcite, hence possibly favoring the growth of the HAP layer. Finally, a double application of the treatment was tested. Results were compared to those obtained with ammonium oxalate treatment, widely investigated for marble protection. Results indicate that adding small amounts of ethanol to the formulation remarkably increases the acid resistance of treated samples, and yields better coverage of the surface without crack formation. The effectiveness of the treatment is further enhanced when a second treatment is applied. The efficacy of ethanol-doped DAP mixtures was found to be remarkably higher than that of ammonium oxalate based treatments.

Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes.

PubMed

Evans, Steven T; Stewart, Kevin D; Afdahl, Chris; Patel, Rohan; Newell, Kelcy J

2017-07-14

In this paper, we discuss the optimization and implementation of a high throughput process development (HTPD) tool that utilizes commercially available micro-liter sized column technology for the purification of multiple clinically significant monoclonal antibodies. Chromatographic profiles generated using this optimized tool are shown to overlay with comparable profiles from the conventional bench-scale and clinical manufacturing scale. Further, all product quality attributes measured are comparable across scales for the mAb purifications. In addition to supporting chromatography process development efforts (e.g., optimization screening), comparable product quality results at all scales makes this tool is an appropriate scale model to enable purification and product quality comparisons of HTPD bioreactors conditions. The ability to perform up to 8 chromatography purifications in parallel with reduced material requirements per run creates opportunities for gathering more process knowledge in less time. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Optimizing chemical conditioning for odour removal of undigested sewage sludge in drying processes.

PubMed

Vega, Esther; Monclús, Hèctor; Gonzalez-Olmos, Rafael; Martin, Maria J

2015-03-01

Emission of odours during the thermal drying in sludge handling processes is one of the main sources of odour problems in wastewater treatment plants. The objective of this work was to assess the use of the response surface methodology as a technique to optimize the chemical conditioning process of undigested sewage sludges, in order to improve the dewaterability, and to reduce the odour emissions during the thermal drying of the sludge. Synergistic effects between inorganic conditioners (iron chloride and calcium oxide) were observed in terms of sulphur emissions and odour reduction. The developed quadratic models indicated that optimizing the conditioners dosage is possible to increase a 70% the dewaterability, reducing a 50% and 54% the emission of odour and volatile sulphur compounds respectively. The optimization of the conditioning process was validated experimentally. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mathematical Analysis and Optimization of Infiltration Processes

NASA Technical Reports Server (NTRS)

Chang, H.-C.; Gottlieb, D.; Marion, M.; Sheldon, B. W.

1997-01-01

A variety of infiltration techniques can be used to fabricate solid materials, particularly composites. In general these processes can be described with at least one time dependent partial differential equation describing the evolution of the solid phase, coupled to one or more partial differential equations describing mass transport through a porous structure. This paper presents a detailed mathematical analysis of a relatively simple set of equations which is used to describe chemical vapor infiltration. The results demonstrate that the process is controlled by only two parameters, alpha and beta. The optimization problem associated with minimizing the infiltration time is also considered. Allowing alpha and beta to vary with time leads to significant reductions in the infiltration time, compared with the conventional case where alpha and beta are treated as constants.

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

Magnetic manipulation device for the optimization of cell processing conditions.

PubMed

Ito, Hiroshi; Kato, Ryuji; Ino, Kosuke; Honda, Hiroyuki

2010-02-01

Variability in human cell phenotypes make it's advancements in optimized cell processing necessary for personalized cell therapy. Here we propose a strategy of palm-top sized device to assist physically manipulating cells for optimizing cell preparations. For the design of such a device, we combined two conventional approaches: multi-well plate formatting and magnetic cell handling using magnetite cationic liposomes (MCLs). From our previous works, we showed the labeling applications of MCL on adhesive cells for various tissue engineering approaches. To feasibly transfer cells in multi-well plate, we here evaluated the magnetic response of MCL-labeled suspension type cells. The cell handling performance of Jurkat cells proved to be faster and more robust compared to MACS (Magnetic Cell Sorting) bead methods. To further confirm our strategy, prototype palm-top sized device "magnetic manipulation device (MMD)" was designed. In the device, the actual cell transportation efficacy of Jurkat cells was satisfying. Moreover, as a model of the most distributed clinical cell processing, primary peripheral blood mononuclear cells (PBMCs) from different volunteers were evaluated. By MMD, individual PBMCs indicated to have optimum Interleukin-2 (IL-2) concentrations for the expansion. Such huge differences of individual cells indicated that MMD, our proposing efficient and self-contained support tool, could assist the feasible and cost-effective optimization of cell processing in clinical facilities. Copyright (c) 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Simulation based optimization on automated fibre placement process

NASA Astrophysics Data System (ADS)

Lei, Shi

2018-02-01

In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

Molecular identification of potential denitrifying bacteria and use of D-optimal mixture experimental design for the optimization of denitrification process.

PubMed

Ben Taheur, Fadia; Fdhila, Kais; Elabed, Hamouda; Bouguerra, Amel; Kouidhi, Bochra; Bakhrouf, Amina; Chaieb, Kamel

2016-04-01

Three bacterial strains (TE1, TD3 and FB2) were isolated from date palm (degla), pistachio and barley. The presence of nitrate reductase (narG) and nitrite reductase (nirS and nirK) genes in the selected strains was detected by PCR technique. Molecular identification based on 16S rDNA sequencing method was applied to identify positive strains. In addition, the D-optimal mixture experimental design was used to optimize the optimal formulation of probiotic bacteria for denitrification process. Strains harboring denitrification genes were identified as: TE1, Agrococcus sp LN828197; TD3, Cronobacter sakazakii LN828198 and FB2, Pedicoccus pentosaceus LN828199. PCR results revealed that all strains carried the nirS gene. However only C. sakazakii LN828198 and Agrococcus sp LN828197 harbored the nirK and the narG genes respectively. Moreover, the studied bacteria were able to form biofilm on abiotic surfaces with different degree. Process optimization showed that the most significant reduction of nitrate was 100% with 14.98% of COD consumption and 5.57 mg/l nitrite accumulation. Meanwhile, the response values were optimized and showed that the most optimal combination was 78.79% of C. sakazakii LN828198 (curve value), 21.21% of P. pentosaceus LN828199 (curve value) and absence (0%) of Agrococcus sp LN828197 (curve value). Copyright © 2016 Elsevier Ltd. All rights reserved.

Combining analysis with optimization at Langley Research Center. An evolutionary process

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.

1982-01-01

The evolutionary process of combining analysis and optimization codes was traced with a view toward providing insight into the long term goal of developing the methodology for an integrated, multidisciplinary software system for the concurrent analysis and optimization of aerospace structures. It was traced along the lines of strength sizing, concurrent strength and flutter sizing, and general optimization to define a near-term goal for combining analysis and optimization codes. Development of a modular software system combining general-purpose, state-of-the-art, production-level analysis computer programs for structures, aerodynamics, and aeroelasticity with a state-of-the-art optimization program is required. Incorporation of a modular and flexible structural optimization software system into a state-of-the-art finite element analysis computer program will facilitate this effort. This effort results in the software system used that is controlled with a special-purpose language, communicates with a data management system, and is easily modified for adding new programs and capabilities. A 337 degree-of-freedom finite element model is used in verifying the accuracy of this system.

MO-B-BRB-00: Optimizing the Treatment Planning Process

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

NONE

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequentialmore » events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d

"Just another hoop to jump through?" using environmental laws and processes to protect indigenous rights.

PubMed

Middleton, Beth Rose

2013-11-01

Protection of culturally important indigenous landscapes has become an increasingly important component of environmental management processes, for both companies and individuals striving to comply with environmental regulations, and for indigenous groups seeking stronger laws to support site protection and cultural/human rights. Given that indigenous stewardship of culturally important sites, species, and practices continues to be threatened or prohibited on lands out of indigenous ownership, this paper examines whether or not indigenous people can meaningfully apply mainstream environmental management laws and processes to achieve protection of traditional sites and associated stewardship activities. While environmental laws can provide a "back door" to protect traditional sites and practices, they are not made for this purpose, and, as such, require specific amendments to become more useful for indigenous practitioners. Acknowledging thoughtful critiques of the cultural incommensurability of environmental law with indigenous environmental stewardship of sacred sites, I interrogate the ability of four specific environmental laws and processes-the Uniform Conservation Easement Act; the National Environmental Policy Act and the California Environmental Quality Act; the Pacific Stewardship Council land divestiture process; and Senate Bill 18 (CA-2004)-to protect culturally important landscapes and practices. I offer suggestions for improving these laws and processes to make them more applicable to indigenous stewardship of traditional landscapes.

Process optimization of rolling for zincked sheet technology using response surface methodology and genetic algorithm

NASA Astrophysics Data System (ADS)

Ji, Liang-Bo; Chen, Fang

2017-07-01

Numerical simulation and intelligent optimization technology were adopted for rolling and extrusion of zincked sheet. By response surface methodology (RSM), genetic algorithm (GA) and data processing technology, an efficient optimization of process parameters for rolling of zincked sheet was investigated. The influence trend of roller gap, rolling speed and friction factor effects on reduction rate and plate shortening rate were analyzed firstly. Then a predictive response surface model for comprehensive quality index of part was created using RSM. Simulated and predicted values were compared. Through genetic algorithm method, the optimal process parameters for the forming of rolling were solved. They were verified and the optimum process parameters of rolling were obtained. It is feasible and effective.

Lithographic process window optimization for mask aligner proximity lithography

NASA Astrophysics Data System (ADS)

Voelkel, Reinhard; Vogler, Uwe; Bramati, Arianna; Erdmann, Andreas; Ünal, Nezih; Hofmann, Ulrich; Hennemeyer, Marc; Zoberbier, Ralph; Nguyen, David; Brugger, Juergen

2014-03-01

We introduce a complete methodology for process window optimization in proximity mask aligner lithography. The commercially available lithography simulation software LAB from GenISys GmbH was used for simulation of light propagation and 3D resist development. The methodology was tested for the practical example of lines and spaces, 5 micron half-pitch, printed in a 1 micron thick layer of AZ® 1512HS1 positive photoresist on a silicon wafer. A SUSS MicroTec MA8 mask aligner, equipped with MO Exposure Optics® was used in simulation and experiment. MO Exposure Optics® is the latest generation of illumination systems for mask aligners. MO Exposure Optics® provides telecentric illumination and excellent light uniformity over the full mask field. MO Exposure Optics® allows the lithography engineer to freely shape the angular spectrum of the illumination light (customized illumination), which is a mandatory requirement for process window optimization. Three different illumination settings have been tested for 0 to 100 micron proximity gap. The results obtained prove, that the introduced process window methodology is a major step forward to obtain more robust processes in mask aligner lithography. The most remarkable outcome of the presented study is that a smaller exposure gap does not automatically lead to better print results in proximity lithography - what the "good instinct" of a lithographer would expect. With more than 5'000 mask aligners installed in research and industry worldwide, the proposed process window methodology might have significant impact on yield improvement and cost saving in industry.

Optimization of a Sample Processing Protocol for Recovery of ...

EPA Pesticide Factsheets

Journal Article Following a release of Bacillus anthracis spores into the environment, there is a potential for lasting environmental contamination in soils. There is a need for detection protocols for B. anthracis in environmental matrices. However, identification of B. anthracis within a soil is a difficult task. Processing soil samples helps to remove debris, chemical components, and biological impurities that can interfere with microbiological detection. This study aimed to optimize a previously used indirect processing protocol, which included a series of washing and centrifugation steps.

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).

Clinical application of 'Justification' and 'Optimization' principle of ALARA in pediatric CT imaging: "How many children can be protected from unnecessary radiation?".

PubMed

Sodhi, Kushaljit S; Krishna, Satheesh; Saxena, Akshay K; Sinha, Anindita; Khandelwal, Niranjan; Lee, Edward Y

2015-09-01

Practice of ALARA (as low as reasonably achievable) principle in the developed world is currently well established. However, there is striking lack of published data regarding such experience in the developing countries. Therefore, the goal of this study is to prospectively evaluate CT request forms to assess how many children could be protected from harmful radiation exposure if 'Justification' and 'Optimization' principles of ALARA are applied before obtaining CT imaging in a developing country. This can save children from potential radiation risks including development of brain cancer and leukemia. Consecutive CT request forms over a six month study period (May 16, 2013 to November 15, 2013) in a tertiary pediatric children's hospital in India were prospectively reviewed by two pediatric radiologists before obtaining CT imaging. First, 'Justification' of CT was evaluated and then 'Optimization' was applied for evaluation of appropriateness of the requested CT studies. The number (and percentage) of CT studies avoided by applying 'Justification' and 'Optimization' principle of ALARA were calculated. The difference in number of declined and optimized CT requests between CT requests from inpatient and outpatient departments was compared using Chi-Square test. A total of 1302 consecutive CT request forms were received during the study period. Some of the request forms (n=86; 6.61%) had requests for more than one (multiple) anatomical regions, hence, a total of 1392 different anatomical CT requests were received. Based on evaluation of the CT request forms for 'Justification' and 'Optimization' principle of ALARA by pediatric radiology reviewers, 111 individual anatomic part CT requests from 105 pediatric patients were avoided. Therefore, 8.06% (105 out of 1302 pediatric patients) were protected from unnecessary or additional radiation exposure.The rates of declined or optimized CT requests from inpatient department was significantly higher than that from outpatient

Switching and optimizing control for coal flotation process based on a hybrid model

PubMed Central

Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

2017-01-01

Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

Derived heuristics-based consistent optimization of material flow in a gold processing plant

NASA Astrophysics Data System (ADS)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Numerical Simulation and Optimization of Directional Solidification Process of Single Crystal Superalloy Casting

PubMed Central

Zhang, Hang; Xu, Qingyan; Liu, Baicheng

2014-01-01

The rapid development of numerical modeling techniques has led to more accurate results in modeling metal solidification processes. In this study, the cellular automaton-finite difference (CA-FD) method was used to simulate the directional solidification (DS) process of single crystal (SX) superalloy blade samples. Experiments were carried out to validate the simulation results. Meanwhile, an intelligent model based on fuzzy control theory was built to optimize the complicate DS process. Several key parameters, such as mushy zone width and temperature difference at the cast-mold interface, were recognized as the input variables. The input variables were functioned with the multivariable fuzzy rule to get the output adjustment of withdrawal rate (v) (a key technological parameter). The multivariable fuzzy rule was built, based on the structure feature of casting, such as the relationship between section area, and the delay time of the temperature change response by changing v, and the professional experience of the operator as well. Then, the fuzzy controlling model coupled with CA-FD method could be used to optimize v in real-time during the manufacturing process. The optimized process was proven to be more flexible and adaptive for a steady and stray-grain free DS process. PMID:28788535

Laser cutting: industrial relevance, process optimization, and laser safety

NASA Astrophysics Data System (ADS)

Haferkamp, Heinz; Goede, Martin; von Busse, Alexander; Thuerk, Oliver

1998-09-01

Compared to other technological relevant laser machining processes, up to now laser cutting is the application most frequently used. With respect to the large amount of possible fields of application and the variety of different materials that can be machined, this technology has reached a stable position within the world market of material processing. Reachable machining quality for laser beam cutting is influenced by various laser and process parameters. Process integrated quality techniques have to be applied to ensure high-quality products and a cost effective use of the laser manufacturing plant. Therefore, rugged and versatile online process monitoring techniques at an affordable price would be desirable. Methods for the characterization of single plant components (e.g. laser source and optical path) have to be substituted by an omnivalent control system, capable of process data acquisition and analysis as well as the automatic adaptation of machining and laser parameters to changes in process and ambient conditions. At the Laser Zentrum Hannover eV, locally highly resolved thermographic measurements of the temperature distribution within the processing zone using cost effective measuring devices are performed. Characteristic values for cutting quality and plunge control as well as for the optimization of the surface roughness at the cutting edges can be deducted from the spatial distribution of the temperature field and the measured temperature gradients. Main influencing parameters on the temperature characteristic within the cutting zone are the laser beam intensity and pulse duration in pulse operation mode. For continuous operation mode, the temperature distribution is mainly determined by the laser output power related to the cutting velocity. With higher cutting velocities temperatures at the cutting front increase, reaching their maximum at the optimum cutting velocity. Here absorption of the incident laser radiation is drastically increased due to

Energy Center Structure Optimization by using Smart Technologies in Process Control System

NASA Astrophysics Data System (ADS)

Shilkina, Svetlana V.

2018-03-01

The article deals with practical application of fuzzy logic methods in process control systems. A control object - agroindustrial greenhouse complex, which includes its own energy center - is considered. The paper analyzes object power supply options taking into account connection to external power grids and/or installation of own power generating equipment with various layouts. The main problem of a greenhouse facility basic process is extremely uneven power consumption, which forces to purchase redundant generating equipment idling most of the time, which quite negatively affects project profitability. Energy center structure optimization is largely based on solving the object process control system construction issue. To cut investor’s costs it was proposed to optimize power consumption by building an energy-saving production control system based on a fuzzy logic controller. The developed algorithm of automated process control system functioning ensured more even electric and thermal energy consumption, allowed to propose construction of the object energy center with a smaller number of units due to their more even utilization. As a result, it is shown how practical use of microclimate parameters fuzzy control system during object functioning leads to optimization of agroindustrial complex energy facility structure, which contributes to a significant reduction in object construction and operation costs.

SU-F-T-201: Acceleration of Dose Optimization Process Using Dual-Loop Optimization Technique for Spot Scanning Proton Therapy

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

Hirayama, S; Fujimoto, R

Purpose: The purpose was to demonstrate a developed acceleration technique of dose optimization and to investigate its applicability to the optimization process in a treatment planning system (TPS) for proton therapy. Methods: In the developed technique, the dose matrix is divided into two parts, main and halo, based on beam sizes. The boundary of the two parts is varied depending on the beam energy and water equivalent depth by utilizing the beam size as a singular threshold parameter. The optimization is executed with two levels of iterations. In the inner loop, doses from the main part are updated, whereas dosesmore » from the halo part remain constant. In the outer loop, the doses from the halo part are recalculated. We implemented this technique to the optimization process in the TPS and investigated the dependence on the target volume of the speedup effect and applicability to the worst-case optimization (WCO) in benchmarks. Results: We created irradiation plans for various cubic targets and measured the optimization time varying the target volume. The speedup effect was improved as the target volume increased, and the calculation speed increased by a factor of six for a 1000 cm3 target. An IMPT plan for the RTOG benchmark phantom was created in consideration of ±3.5% range uncertainties using the WCO. Beams were irradiated at 0, 45, and 315 degrees. The target’s prescribed dose and OAR’s Dmax were set to 3 Gy and 1.5 Gy, respectively. Using the developed technique, the calculation speed increased by a factor of 1.5. Meanwhile, no significant difference in the calculated DVHs was found before and after incorporating the technique into the WCO. Conclusion: The developed technique could be adapted to the TPS’s optimization. The technique was effective particularly for large target cases.« less

Reduced-order model for dynamic optimization of pressure swing adsorption processes

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

Agarwal, A.; Biegler, L.; Zitney, S.

2007-01-01

Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the

USHPRR FUEL FABRICATION PILLAR: FABRICATION STATUS, PROCESS OPTIMIZATIONS, AND FUTURE PLANS

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

Wight, Jared M.; Joshi, Vineet V.; Lavender, Curt A.

The Fuel Fabrication (FF) Pillar, a project within the U.S. High Performance Research Reactor Conversion program of the National Nuclear Security Administration’s Office of Material Management and Minimization, is tasked with the scale-up and commercialization of high-density monolithic U-Mo fuel for the conversion of appropriate research reactors to use of low-enriched fuel. The FF Pillar has made significant steps to demonstrate and optimize the baseline co-rolling process using commercial-scale equipment at both the Y-12 National Security Complex (Y-12) and BWX Technologies (BWXT). These demonstrations include the fabrication of the next irradiation experiment, Mini-Plate 1 (MP-1), and casting optimizations at Y-12.more » The FF Pillar uses a detailed process flow diagram to identify potential gaps in processing knowledge or demonstration, which helps direct the strategic research agenda of the FF Pillar. This paper describes the significant progress made toward understanding the fuel characteristics, and models developed to make informed decisions, increase process yield, and decrease lifecycle waste and costs.« less

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms.

PubMed

Andrés-Toro, B; Girón-Sierra, J M; Fernández-Blanco, P; López-Orozco, J A; Besada-Portas, E

2004-04-01

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.

[Coupling AFM fluid imaging with micro-flocculation filtration process for the technological optimization].

PubMed

Zheng, Bei; Ge, Xiao-peng; Yu, Zhi-yong; Yuan, Sheng-guang; Zhang, Wen-jing; Sun, Jing-fang

2012-08-01

Atomic force microscope (AFM) fluid imaging was applied to the study of micro-flocculation filtration process and the optimization of micro-flocculation time and the agitation intensity of G values. It can be concluded that AFM fluid imaging proves to be a promising tool in the observation and characterization of floc morphology and the dynamic coagulation processes under aqueous environmental conditions. Through the use of AFM fluid imaging technique, optimized conditions for micro-flocculation time of 2 min and the agitation intensity (G value) of 100 s(-1) were obtained in the treatment of dye-printing industrial tailing wastewater by the micro-flocculation filtration process with a good performance.

Optimal conditions of LDR to protect the kidney from diabetes: exposure to 12.5 mGy X-rays for 8 weeks efficiently protects the kidney from diabetes.

PubMed

Cheng, Jie; Li, Fengsheng; Cui, Jiuwei; Guo, Weiying; Li, Cai; Li, Wei; Wang, Guixia; Xing, Xiao; Gao, Ying; Ge, Yuanyuan; Wang, Guanjun; Cai, Lu

2014-05-08

We reported the attenuation of diabetes-induced renal dysfunction by exposure to multiple low-dose radiation (LDR) at 25 mGy every other day by suppressing renal oxidative damage. We here explored the optimal conditions of LDR to protect the kidney from diabetes. Male C57BL/6J mice with type 1 diabetes were induced with multiple injections of low-dose streptozotocin. Diabetic mice received whole body X-irradiation at a dose of 12.5, 25 or 50 mGy every other day for either 4 or 8 weeks. Age-matched normal mice were similarly irradiated at the dose of 25 mGy for 4 or 8 weeks. The renal function and histopathological changes were examined at the 4th and 8th weeks of the study. Diabetes induced renal dysfunction is shown by the decreased creatinine and increased microalbumin in the urine. Renal oxidative damage, detected by protein nitration and lipid oxidation, and remodeling, reflected by increased expression of connective tissue growth factor, collagen IV and fibronectin, were significantly increased in diabetic mice. All these renal pathological and function changes in diabetic mice were significantly attenuated by exposure to LDR at all regimens, among which, however, exposure to LDR at 12.5 mGy for 8 weeks provided the best protective effect on the kidney of diabetic mice. Our results suggest that whole-body LDR at 12.5 mGy every other day for 8 weeks is the optimal condition of LDR to protect the kidney from diabetes. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

Process optimization electrospinning fibrous material based on polyhydroxybutyrate

NASA Astrophysics Data System (ADS)

Olkhov, A. A.; Tyubaeva, P. M.; Staroverova, O. V.; Mastalygina, E. E.; Popov, A. A.; Ischenko, A. A.; Iordanskii, A. L.

2016-05-01

The article analyzes the influence of the main technological parameters of electrostatic spinning on the morphology and properties of ultrathin fibers on the basis of polyhydroxybutyrate. It is found that the electric conductivity and viscosity of the spinning solution affects the process of forming fibers macrostructure. The fiber-based materials PHB lets control geometry and optimize the viscosity and conductivity of a spinning solution. The resulting fibers have found use in medicine, particularly in the construction elements musculoskeletal.

Optimal and centralized reservoir management for drought and flood protection via Stochastic Dual Dynamic Programming on the Upper Seine-Aube River system

NASA Astrophysics Data System (ADS)

Chiavico, Mattia; Raso, Luciano; Dorchies, David; Malaterre, Pierre-Olivier

2015-04-01

Seine river region is an extremely important logistic and economic junction for France and Europe. The hydraulic protection of most part of the region relies on four controlled reservoirs, managed by EPTB Seine-Grands Lacs. Presently, reservoirs operation is not centrally coordinated, and release rules are based on empirical filling curves. In this study, we analyze how a centralized release policy can face flood and drought risks, optimizing water system efficiency. The optimal and centralized decisional problem is solved by Stochastic Dual Dynamic Programming (SDDP) method, minimizing an operational indicator for each planning objective. SDDP allows us to include into the system: 1) the hydrological discharge, specifically a stochastic semi-distributed auto-regressive model, 2) the hydraulic transfer model, represented by a linear lag and route model, and 3) reservoirs and diversions. The novelty of this study lies on the combination of reservoir and hydraulic models in SDDP for flood and drought protection problems. The study case covers the Seine basin until the confluence with Aube River: this system includes two reservoirs, the city of Troyes, and the Nuclear power plant of Nogent-Sur-Seine. The conflict between the interests of flood protection, drought protection, water use and ecology leads to analyze the environmental system in a Multi-Objective perspective.

Topography-based Flood Planning and Optimization Capability Development Report

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

Judi, David R.; Tasseff, Byron A.; Bent, Russell W.

2014-02-26

Globally, water-related disasters are among the most frequent and costly natural hazards. Flooding inflicts catastrophic damage on critical infrastructure and population, resulting in substantial economic and social costs. NISAC is developing LeveeSim, a suite of nonlinear and network optimization models, to predict optimal barrier placement to protect critical regions and infrastructure during flood events. LeveeSim currently includes a high-performance flood model to simulate overland flow, as well as a network optimization model to predict optimal barrier placement during a flood event. The LeveeSim suite models the effects of flooding in predefined regions. By manipulating a domain’s underlying topography, developers alteredmore » flood propagation to reduce detrimental effects in areas of interest. This numerical altering of a domain’s topography is analogous to building levees, placing sandbags, etc. To induce optimal changes in topography, NISAC used a novel application of an optimization algorithm to minimize flooding effects in regions of interest. To develop LeveeSim, NISAC constructed and coupled hydrodynamic and optimization algorithms. NISAC first implemented its existing flood modeling software to use massively parallel graphics processing units (GPUs), which allowed for the simulation of larger domains and longer timescales. NISAC then implemented a network optimization model to predict optimal barrier placement based on output from flood simulations. As proof of concept, NISAC developed five simple test scenarios, and optimized topographic solutions were compared with intuitive solutions. Finally, as an early validation example, barrier placement was optimized to protect an arbitrary region in a simulation of the historic Taum Sauk dam breach.« less

Performance improvements of binary diffractive structures via optimization of the photolithography and dry etch processes

NASA Astrophysics Data System (ADS)

Welch, Kevin; Leonard, Jerry; Jones, Richard D.

2010-08-01

Increasingly stringent requirements on the performance of diffractive optical elements (DOEs) used in wafer scanner illumination systems are driving continuous improvements in their associated manufacturing processes. Specifically, these processes are designed to improve the output pattern uniformity of off-axis illumination systems to minimize degradation in the ultimate imaging performance of a lithographic tool. In this paper, we discuss performance improvements in both photolithographic patterning and RIE etching of fused silica diffractive optical structures. In summary, optimized photolithographic processes were developed to increase critical dimension uniformity and featuresize linearity across the substrate. The photoresist film thickness was also optimized for integration with an improved etch process. This etch process was itself optimized for pattern transfer fidelity, sidewall profile (wall angle, trench bottom flatness), and across-wafer etch depth uniformity. Improvements observed with these processes on idealized test structures (for ease of analysis) led to their implementation in product flows, with comparable increases in performance and yield on customer designs.

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A Framework to Design and Optimize Chemical Flooding Processes

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

``Just Another Hoop to Jump Through?'' Using Environmental Laws and Processes to Protect Indigenous Rights

NASA Astrophysics Data System (ADS)

Middleton, Beth Rose

2013-11-01

Protection of culturally important indigenous landscapes has become an increasingly important component of environmental management processes, for both companies and individuals striving to comply with environmental regulations, and for indigenous groups seeking stronger laws to support site protection and cultural/human rights. Given that indigenous stewardship of culturally important sites, species, and practices continues to be threatened or prohibited on lands out of indigenous ownership, this paper examines whether or not indigenous people can meaningfully apply mainstream environmental management laws and processes to achieve protection of traditional sites and associated stewardship activities. While environmental laws can provide a “back door” to protect traditional sites and practices, they are not made for this purpose, and, as such, require specific amendments to become more useful for indigenous practitioners. Acknowledging thoughtful critiques of the cultural incommensurability of environmental law with indigenous environmental stewardship of sacred sites, I interrogate the ability of four specific environmental laws and processes—the Uniform Conservation Easement Act; the National Environmental Policy Act and the California Environmental Quality Act; the Pacific Stewardship Council land divestiture process; and Senate Bill 18 (CA-2004)—to protect culturally important landscapes and practices. I offer suggestions for improving these laws and processes to make them more applicable to indigenous stewardship of traditional landscapes.

Optimization of coastal protection measures on small islands in the northfrisian part of the North Sea

NASA Astrophysics Data System (ADS)

Wöffler, T.; Jensen, J.; Schüttrumpf, H.

2017-12-01

Low lying small islands are among the most vulnerable regions worldwide due to the consequences of climate change. The reasons for this are the concentration of infrastructure, geographical features and their small size. Worldwide special forms and adaptations of coastal protection strategies and measures can be found on small islands. In the northfrisian part of the North Sea worldwide unique strategies and measures have been developed in the last centuries due to the geographic location and the isolation during extreme events. One special feature of their coastal protection strategy is the lack of dikes. For this reason, the houses are built on artificial dwelling mounds in order to protect the inhabitants and their goods against frequently occurring inundations during storm surge seasons (up to 30 times a year). The Hallig islands themselves benefit by these inundations due to sediments, which are accumulated on the island's surfaces. This sedimentation has enabled a natural adaption to sea level rise in the past. Nevertheless, the construction methods of the coastal protection measures are mainly based on tradition and the knowledge of the inhabitants. No resilient design approaches and safety standards for these special structures like dwelling mounds and elevated revetments exist today. For this reason, neither a cost efficient construction nor a prioritization of measures is possible. Main part of this paper is the scientific investigation of the existing coastal protection measures with the objective of the development of design approaches and safety standards. The results will optimize the construction of the existing coastal protection measures and can be transferred to other small islands and low lying areas worldwide.

Optimization of a novel enzyme treatment process for early-stage processing of sheepskins.

PubMed

Lim, Y F; Bronlund, J E; Allsop, T F; Shilton, A N; Edmonds, R L

2010-01-01

An enzyme treatment process for early-stage processing of sheepskins has been previously reported by the Leather and Shoe Research Association of New Zealand (LASRA) as an alternative to current industry operations. The newly developed process had marked benefits over conventional processing in terms of a lowered energy usage (73%), processing time (47%) as well as water use (49%), but had been developed as a "proof of principle''. The objective of this work was to develop the process further to a stage ready for adoption by industry. Mass balancing was used to investigate potential modifications for the process based on the understanding developed from a detailed analysis of preliminary design trials. Results showed that a configuration utilising a 2 stage counter-current system for the washing stages and segregation and recycling of enzyme float prior to dilution in the neutralization stage was a significant improvement. Benefits over conventional processing include a reduction of residual TDS by 50% at the washing stages and 70% savings on water use overall. Benefits over the un-optimized LASRA process are reduction of solids in product after enzyme treatment and neutralization stages by 30%, additional water savings of 21%, as well as 10% savings of enzyme usage.

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.

Toxicity assessment of tannery effluent treated by an optimized photo-Fenton process.

PubMed

Borba, Fernando Henrique; Módenes, Aparecido Nivaldo; Espinoza-Quiñones, Fernando Rodolfo; Manenti, Diego Ricieri; Bergamasco, Rosangela; Mora, Nora Diaz

2013-01-01

In this work, an optimized photo-Fenton process was applied to remove pollutants from tannery industrial effluent (TIE) with its final toxicity level being assessed by a lettuce-seed-based bioassay test. A full 33 factorial design was applied for the optimization of long-term photo-Fenton experiments. The oPtimum conditions of the photo-Fenton process were attained at concentration values of 0.3 g Fe(2+) L(-1) and 20 g H2O2 L(-1) and pH3, for 120 min UV irradiation time. Reactor operating parameter (ROP) effects on the removal of chemical oxygen demand, colour, turbidity, total suspended solids and total volatile solids were evaluated, suggesting that a broad range of ROP values are also suitable to give results very near to those of the photo-Fenton experiments under optimal conditions. Based on the low calculated median lethal dose (LD50) values from a lettuce-seed-based bioassay test, we suggest that recalcitrant substances are present in treated TIE samples. A possible cause of the high toxicity level could partly be attributed to the nitrate concentration, which was not completely abated by the photo-Fenton process. Apart from this, the photo-Fenton process can be used as a part of an industrial effluent treatment system in order to abate high organic pollutant loads.

Fire Hazard Assessment in Supporting Fire Protection System Design of a Chemical Process Facility

DTIC Science & Technology

1996-08-01

CSDP/Studies/FireHaz –i– 3/28/97 FIRE HAZARD ASSESSMENT IN SUPPORTING FIRE PROTECTION SYSTEM DESIGN OF A CHEMICAL PROCESS FACILITY Ali Pezeshk...Joseph Chang, Dwight Hunt, and Peter Jahn Parsons Infrastructure & Technology Group, Inc. Pasadena, California 91124 ABSTRACT Because fires in a chemical ...Assessment in Supporting Fire Protection System Design of a Chemical Process Facility 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

The Study on the Optimization of Container Multimodal Transport Business Process in Shandong

NASA Astrophysics Data System (ADS)

Wang, Fengmei; Gong, Xiaoyi; Ni, Yingying; Zhan, Jun; Che, Huiping

2018-06-01

Shandong is a coastal city with good location advantages. As a hub port for international trade goods and a port of transhipment, shandong's demand for multimodal transport is more urgent. By selecting the suitable non-water port and the multimodal transport carrier to improve the efficiency of multimodal transport, the purpose of saving the time of logistics is achieved, thus reducing the logistics cost.It branch out through Shandongt, and it can reach the central region of China, can reach the Western remote area ,too. This paper puts forward the optimization scheme of the business process of container multimodal transport. The optimization of freight forwarding business process is analyzed. The multimodal transport model in Shandong was designed. Finally, the optimal approach of multimodal transport in Shandong is put forward.

About Distributed Simulation-based Optimization of Forming Processes using a Grid Architecture

NASA Astrophysics Data System (ADS)

Grauer, Manfred; Barth, Thomas

2004-06-01

Permanently increasing complexity of products and their manufacturing processes combined with a shorter "time-to-market" leads to more and more use of simulation and optimization software systems for product design. Finding a "good" design of a product implies the solution of computationally expensive optimization problems based on the results of simulation. Due to the computational load caused by the solution of these problems, the requirements on the Information&Telecommunication (IT) infrastructure of an enterprise or research facility are shifting from stand-alone resources towards the integration of software and hardware resources in a distributed environment for high-performance computing. Resources can either comprise software systems, hardware systems, or communication networks. An appropriate IT-infrastructure must provide the means to integrate all these resources and enable their use even across a network to cope with requirements from geographically distributed scenarios, e.g. in computational engineering and/or collaborative engineering. Integrating expert's knowledge into the optimization process is inevitable in order to reduce the complexity caused by the number of design variables and the high dimensionality of the design space. Hence, utilization of knowledge-based systems must be supported by providing data management facilities as a basis for knowledge extraction from product data. In this paper, the focus is put on a distributed problem solving environment (PSE) capable of providing access to a variety of necessary resources and services. A distributed approach integrating simulation and optimization on a network of workstations and cluster systems is presented. For geometry generation the CAD-system CATIA is used which is coupled with the FEM-simulation system INDEED for simulation of sheet-metal forming processes and the problem solving environment OpTiX for distributed optimization.

Habitat Design Optimization and Analysis

NASA Technical Reports Server (NTRS)

SanSoucie, Michael P.; Hull, Patrick V.; Tinker, Michael L.

2006-01-01

Long-duration surface missions to the Moon and Mars will require habitats for the astronauts. The materials chosen for the habitat walls play a direct role in the protection against the harsh environments found on the surface. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. Advanced optimization techniques are necessary for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces; therefore, a habitat design optimization tool utilizing genetic algorithms has been developed. Genetic algorithms use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce. This habitat design optimization tool is a multi-objective formulation of structural analysis, heat loss, radiation protection, and meteoroid protection. This paper presents the research and development of this tool.

Multi-objective Optimization of Pulsed Gas Metal Arc Welding Process Using Neuro NSGA-II

NASA Astrophysics Data System (ADS)

Pal, Kamal; Pal, Surjya K.

2018-05-01

Weld quality is a critical issue in fabrication industries where products are custom-designed. Multi-objective optimization results number of solutions in the pareto-optimal front. Mathematical regression model based optimization methods are often found to be inadequate for highly non-linear arc welding processes. Thus, various global evolutionary approaches like artificial neural network, genetic algorithm (GA) have been developed. The present work attempts with elitist non-dominated sorting GA (NSGA-II) for optimization of pulsed gas metal arc welding process using back propagation neural network (BPNN) based weld quality feature models. The primary objective to maintain butt joint weld quality is the maximization of tensile strength with minimum plate distortion. BPNN has been used to compute the fitness of each solution after adequate training, whereas NSGA-II algorithm generates the optimum solutions for two conflicting objectives. Welding experiments have been conducted on low carbon steel using response surface methodology. The pareto-optimal front with three ranked solutions after 20th generations was considered as the best without further improvement. The joint strength as well as transverse shrinkage was found to be drastically improved over the design of experimental results as per validated pareto-optimal solutions obtained.

Metamodeling and optimization of the THF process with pulsating pressure

NASA Astrophysics Data System (ADS)

Bucconi, Marco; Strano, Matteo

2018-05-01

Tube hydroforming is a process used in various applications to form the tube in a desired complex shape, by combining the use of internal pressure, which provides the required stress to yield the material, and axial feeding, which helps the material to flow towards the bulging zone. In many studies it has been demonstrated how wrinkling and bursting defects can be severely reduced by means of a pulsating pressure, and how the so-called hammering hydroforming enhances the formability of the material. The definition of the optimum pressure and axial feeding profiles represent a daunting challenge in the designing phase of the hydroforming operation of a new part. The quality of the formed part is highly dependent on the amplitude and the peak value of the pulsating pressure, along with the axial stroke. In this paper, a research is reported, conducted by means of explicit finite element simulations of a hammering THF operation and metamodeling techniques aimed at optimizing the process parameters for the production of a complex part. The improved formability is explored for different factors and an optimization strategy is used to determine the most convenient pressure and axial feed profile curves for the hammering THF process of the examined part. It is shown how the pulsating pressure allows the minimization of the energy input in the process, still respecting final quality requirements.

Optimization of a thermal hydrolysis process for sludge pre-treatment.

PubMed

Sapkaite, I; Barrado, E; Fdz-Polanco, F; Pérez-Elvira, S I

2017-05-01

At industrial scale, thermal hydrolysis is the most used process to enhance biodegradability of the sludge produced in wastewater treatment plants. Through statistically guided Box-Behnken experimental design, the present study analyses the effect of TH as pre-treatment applied to activated sludge. The selected process variables were temperature (130-180 °C), time (5-50 min) and decompression mode (slow or steam-explosion effect), and the parameters evaluated were sludge solubilisation and methane production by anaerobic digestion. A quadratic polynomial model was generated to compare the process performance for the 15 different combinations of operation conditions by modifying the process variables evaluated. The statistical analysis performed exhibited that methane production and solubility were significantly affected by pre-treatment time and temperature. During high intensity pre-treatment (high temperature and long times), the solubility increased sharply while the methane production exhibited the opposite behaviour, indicating the formation of some soluble but non-biodegradable materials. Therefore, solubilisation is not a reliable parameter to quantify the efficiency of a thermal hydrolysis pre-treatment, since it is not directly related to methane production. Based on the operational parameters optimization, the estimated optimal thermal hydrolysis conditions to enhance of sewage sludge digestion were: 140-170 °C heating temperature, 5-35min residence time, and one sudden decompression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling and optimization of semi-solid processing of 7075 Al alloy

NASA Astrophysics Data System (ADS)

Binesh, B.; Aghaie-Khafri, M.

2017-09-01

The new modified strain-induced melt activation (SIMA) process presented by Binesh and Aghaie-Khafri was optimized using a response surface methodology to improve the thixotropic characteristics of semi-solid 7075 alloy. The responses, namely the average grain size and the shape factor, were considered as functions of three independent input variables: effective strain, isothermal holding temperature and time. Mathematical models for the responses were developed using the regression analysis technique, and the adequacy of the models was validated by the analysis of variance method. The calculated results correlated fairly well with the experiments. It was found that all the first- and second-order terms of the independent parameters and the interactive terms of the effective strain and holding time were statistically significant for the responses. In order to simultaneously optimize the responses, the desirable values for the effective strain, holding temperature and time were predicted to be 5.1, 609 °C and 14 min, respectively, when employing the desirability function approach. Based on the optimization results, a significant improvement in the average grain size and shape factor of the semi-solid slurry prepared by the new modified SIMA process was observed.

Minimizing transient influence in WHPA delineation: An optimization approach for optimal pumping rate schemes

NASA Astrophysics Data System (ADS)

Rodriguez-Pretelin, A.; Nowak, W.

2017-12-01

For most groundwater protection management programs, Wellhead Protection Areas (WHPAs) have served as primarily protection measure. In their delineation, the influence of time-varying groundwater flow conditions is often underestimated because steady-state assumptions are commonly made. However, it has been demonstrated that temporary variations lead to significant changes in the required size and shape of WHPAs. Apart from natural transient groundwater drivers (e.g., changes in the regional angle of flow direction and seasonal natural groundwater recharge), anthropogenic causes such as transient pumping rates are of the most influential factors that require larger WHPAs. We hypothesize that WHPA programs that integrate adaptive and optimized pumping-injection management schemes can counter transient effects and thus reduce the additional areal demand in well protection under transient conditions. The main goal of this study is to present a novel management framework that optimizes pumping schemes dynamically, in order to minimize the impact triggered by transient conditions in WHPA delineation. For optimizing pumping schemes, we consider three objectives: 1) to minimize the risk of pumping water from outside a given WHPA, 2) to maximize the groundwater supply and 3) to minimize the involved operating costs. We solve transient groundwater flow through an available transient groundwater and Lagrangian particle tracking model. The optimization problem is formulated as a dynamic programming problem. Two different optimization approaches are explored: I) the first approach aims for single-objective optimization under objective (1) only. The second approach performs multiobjective optimization under all three objectives where compromise pumping rates are selected from the current Pareto front. Finally, we look for WHPA outlines that are as small as possible, yet allow the optimization problem to find the most suitable solutions.

Affordable Design: A Methodolgy to Implement Process-Based Manufacturing Cost into the Traditional Performance-Focused Multidisciplinary Design Optimization

NASA Technical Reports Server (NTRS)

Bao, Han P.; Samareh, J. A.

2000-01-01

The primary objective of this paper is to demonstrate the use of process-based manufacturing and assembly cost models in a traditional performance-focused multidisciplinary design and optimization process. The use of automated cost-performance analysis is an enabling technology that could bring realistic processbased manufacturing and assembly cost into multidisciplinary design and optimization. In this paper, we present a new methodology for incorporating process costing into a standard multidisciplinary design optimization process. Material, manufacturing processes, and assembly processes costs then could be used as the objective function for the optimization method. A case study involving forty-six different configurations of a simple wing is presented, indicating that a design based on performance criteria alone may not necessarily be the most affordable as far as manufacturing and assembly cost is concerned.

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

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.

Technical and economical optimization of a full-scale poultry manure treatment process: total ammonia nitrogen balance.

PubMed

Alejo-Alvarez, Luz; Guzmán-Fierro, Víctor; Fernández, Katherina; Roeckel, Marlene

2016-11-01

A full-scale process for the treatment of 80 tons per day of poultry manure was designed and optimized. A total ammonia nitrogen (TAN) balance was performed at steady state, considering the stoichiometry and the kinetic data from the anaerobic digestion and the anaerobic ammonia oxidation. The equipment, reactor design, investment costs, and operational costs were considered. The volume and cost objective functions optimized the process in terms of three variables: the water recycle ratio, the protein conversion during AD, and the TAN conversion in the process. The processes were compared with and without water recycle; savings of 70% and 43% in the annual fresh water consumption and the heating costs, respectively, were achieved. The optimal process complies with the Chilean environmental legislation limit of 0.05 g total nitrogen/L.

Optimization of an asymmetric thin-walled tube in rotary draw bending process

NASA Astrophysics Data System (ADS)

Xue, Xin; Liao, Juan; Vincze, Gabriela; Gracio, Jose J.

2013-12-01

The rotary draw bending is one of the advanced thin-walled tube forming processes with high efficiency, low consumption and good flexibility in several industries such as automotive, aerospace and shipping. However it may cause undesirable deformations such as over-thinning and ovalization, which bring the weakening of the strength and difficulties in the assembly process respectively. Accurate modeling and effective optimization design to eliminate or reduce undesirable deformations in tube bending process have been a challenging topic. In this paper, in order to study the deformation behaviors of an asymmetric thin-walled tube in rotary draw bending process, a 3D elastic-plastic finite element model has been built under the ABAQUS environment, and the reliability of the model is validated by comparison with experiment. Then, the deformation mechanism of thin-walled tube in bending process was briefly analysis and the effects of wall thickness ratio, section height width ratio and mandrel extension on wall thinning and ovalization in bending process were investigated by using Response Surface Methodology. Finally, multi-objective optimization method was used to obtain an optimum solution of design variables based on simulation results.

Development of optimization model for sputtering process parameter based on gravitational search algorithm

NASA Astrophysics Data System (ADS)

Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

2016-07-01

In the RF magnetron sputtering process, the desirable layer properties are largely influenced by the process parameters and conditions. If the quality of the thin film has not reached up to its intended level, the experiments have to be repeated until the desirable quality has been met. This research is proposing Gravitational Search Algorithm (GSA) as the optimization model to reduce the time and cost to be spent in the thin film fabrication. The optimization model's engine has been developed using Java. The model is developed based on GSA concept, which is inspired by the Newtonian laws of gravity and motion. In this research, the model is expected to optimize four deposition parameters which are RF power, deposition time, oxygen flow rate and substrate temperature. The results have turned out to be promising and it could be concluded that the performance of the model is satisfying in this parameter optimization problem. Future work could compare GSA with other nature based algorithms and test them with various set of data.

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2001-01-01

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Design Tool Using a New Optimization Method Based on a Stochastic Process

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Yamaguchi, Katsuhito; Ishikawa, Yoshio

Conventional optimization methods are based on a deterministic approach since their purpose is to find out an exact solution. However, such methods have initial condition dependence and the risk of falling into local solution. In this paper, we propose a new optimization method based on the concept of path integrals used in quantum mechanics. The method obtains a solution as an expected value (stochastic average) using a stochastic process. The advantages of this method are that it is not affected by initial conditions and does not require techniques based on experiences. We applied the new optimization method to a hang glider design. In this problem, both the hang glider design and its flight trajectory were optimized. The numerical calculation results prove that performance of the method is sufficient for practical use.

Combined mixture-process variable approach: a suitable statistical tool for nanovesicular systems optimization.

PubMed

Habib, Basant A; AbouGhaly, Mohamed H H

2016-06-01

This study aims to illustrate the applicability of combined mixture-process variable (MPV) design and modeling for optimization of nanovesicular systems. The D-optimal experimental plan studied the influence of three mixture components (MCs) and two process variables (PVs) on lercanidipine transfersomes. The MCs were phosphatidylcholine (A), sodium glycocholate (B) and lercanidipine hydrochloride (C), while the PVs were glycerol amount in the hydration mixture (D) and sonication time (E). The studied responses were Y1: particle size, Y2: zeta potential and Y3: entrapment efficiency percent (EE%). Polynomial equations were used to study the influence of MCs and PVs on each response. Response surface methodology and multiple response optimization were applied to optimize the formulation with the goals of minimizing Y1 and maximizing Y2 and Y3. The obtained polynomial models had prediction R(2) values of 0.645, 0.947 and 0.795 for Y1, Y2 and Y3, respectively. Contour, Piepel's response trace, perturbation, and interaction plots were drawn for responses representation. The optimized formulation, A: 265 mg, B: 10 mg, C: 40 mg, D: zero g and E: 120 s, had desirability of 0.9526. The actual response values for the optimized formulation were within the two-sided 95% prediction intervals and were close to the predicted values with maximum percent deviation of 6.2%. This indicates the validity of combined MPV design and modeling for optimization of transfersomal formulations as an example of nanovesicular systems.

Joint force protection advanced security system (JFPASS) "the future of force protection: integrate and automate"

NASA Astrophysics Data System (ADS)

Lama, Carlos E.; Fagan, Joe E.

2009-09-01

The United States Department of Defense (DoD) defines 'force protection' as "preventive measures taken to mitigate hostile actions against DoD personnel (to include family members), resources, facilities, and critical information." Advanced technologies enable significant improvements in automating and distributing situation awareness, optimizing operator time, and improving sustainability, which enhance protection and lower costs. The JFPASS Joint Capability Technology Demonstration (JCTD) demonstrates a force protection environment that combines physical security and Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) defense through the application of integrated command and control and data fusion. The JFPASS JCTD provides a layered approach to force protection by integrating traditional sensors used in physical security, such as video cameras, battlefield surveillance radars, unmanned and unattended ground sensors. The optimization of human participation and automation of processes is achieved by employment of unmanned ground vehicles, along with remotely operated lethal and less-than-lethal weapon systems. These capabilities are integrated via a tailorable, user-defined common operational picture display through a data fusion engine operating in the background. The combined systems automate the screening of alarms, manage the information displays, and provide assessment and response measures. The data fusion engine links disparate sensors and systems, and applies tailored logic to focus the assessment of events. It enables timely responses by providing the user with automated and semi-automated decision support tools. The JFPASS JCTD uses standard communication/data exchange protocols, which allow the system to incorporate future sensor technologies or communication networks, while maintaining the ability to communicate with legacy or existing systems.

Thermosonication and optimization of stingless bee honey processing.

PubMed

Chong, K Y; Chin, N L; Yusof, Y A

2017-10-01

The effects of thermosonication on the quality of a stingless bee honey, the Kelulut, were studied using processing temperature from 45 to 90 ℃ and processing time from 30 to 120 minutes. Physicochemical properties including water activity, moisture content, color intensity, viscosity, hydroxymethylfurfural content, total phenolic content, and radical scavenging activity were determined. Thermosonication reduced the water activity and moisture content by 7.9% and 16.6%, respectively, compared to 3.5% and 6.9% for conventional heating. For thermosonicated honey, color intensity increased by 68.2%, viscosity increased by 275.0%, total phenolic content increased by 58.1%, and radical scavenging activity increased by 63.0% when compared to its raw form. The increase of hydroxymethylfurfural to 62.46 mg/kg was still within the limits of international standards. Optimized thermosonication conditions using response surface methodology were predicted at 90 ℃ for 111 minutes. Thermosonication was revealed as an effective alternative technique for honey processing.

Optimized adipose tissue engineering strategy based on a neo-mechanical processing method.

PubMed

He, Yunfan; Lin, Maohui; Wang, Xuecen; Guan, Jingyan; Dong, Ziqing; Feng, Lu; Xing, Malcolm; Feng, Chuanbo; Li, Xiaojian

2018-05-26

Decellularized adipose tissue (DAT) represents a promising scaffold for adipose tissue engineering. However, the unique and prolonged lipid removal process required for adipose tissue can damage extracellular matrix (ECM) constituents. Moreover, inadequate vascularization limits the recellularization of DAT in vivo. We proposed a neo-mechanical protocol for rapidly breaking adipocytes and removing lipid content from adipose tissue. The lipid-depleted adipose tissue was then subjected to a fast and mild decellularization to fabricate high-quality DAT (M-DAT). Adipose liquid extract (ALE) derived from this mechanical process was collected and incorporated into M-DAT to further optimize in vivo recellularization. Ordinary DAT was fabricated and served as a control. This developed strategy was evaluated based on decellularization efficiency, ECM quality, and recellularization efficiency. Angiogenic factor components and angiogenic potential of ALE were evaluated in vivo and in vitro. M-DAT achieved the same decellularization efficiency, but exhibited better retention of ECM components and recellularization, compared to those with ordinary DAT. Protein quantification revealed considerable levels of angiogenic factors (basic fibroblast growth factor, epidermal growth factor, transforming growth factor-β1, and vascular endothelial growth factor) in ALE. ALE promoted tube formation in vitro and induced intense angiogenesis in M-DAT in vivo; furthermore, higher expression of the adipogenic factor PPARγ and greater numbers of adipocytes were evident following ALE treatment, compared to those in the M-DAT group. Mechanical processing of adipose tissue led to the production of high-quality M-DAT and angiogenic factor-enriched ALE. The combination of ALE and M-DAT could be a promising strategy for engineered adipose tissue construction. This article is protected by copyright. All rights reserved. © 2018 by the Wound Healing Society.

Combinatorial techniques to efficiently investigate and optimize organic thin film processing and properties.

PubMed

Wieberger, Florian; Kolb, Tristan; Neuber, Christian; Ober, Christopher K; Schmidt, Hans-Werner

2013-04-08

In this article we present several developed and improved combinatorial techniques to optimize processing conditions and material properties of organic thin films. The combinatorial approach allows investigations of multi-variable dependencies and is the perfect tool to investigate organic thin films regarding their high performance purposes. In this context we develop and establish the reliable preparation of gradients of material composition, temperature, exposure, and immersion time. Furthermore we demonstrate the smart application of combinations of composition and processing gradients to create combinatorial libraries. First a binary combinatorial library is created by applying two gradients perpendicular to each other. A third gradient is carried out in very small areas and arranged matrix-like over the entire binary combinatorial library resulting in a ternary combinatorial library. Ternary combinatorial libraries allow identifying precise trends for the optimization of multi-variable dependent processes which is demonstrated on the lithographic patterning process. Here we verify conclusively the strong interaction and thus the interdependency of variables in the preparation and properties of complex organic thin film systems. The established gradient preparation techniques are not limited to lithographic patterning. It is possible to utilize and transfer the reported combinatorial techniques to other multi-variable dependent processes and to investigate and optimize thin film layers and devices for optical, electro-optical, and electronic applications.

Optimization of a sample processing protocol for recovery of Bacillus anthracis spores from soil

USGS Publications Warehouse

Silvestri, Erin E.; Feldhake, David; Griffin, Dale; Lisle, John T.; Nichols, Tonya L.; Shah, Sanjiv; Pemberton, A; Schaefer III, Frank W

2016-01-01

Following a release of Bacillus anthracis spores into the environment, there is a potential for lasting environmental contamination in soils. There is a need for detection protocols for B. anthracis in environmental matrices. However, identification of B. anthracis within a soil is a difficult task. Processing soil samples helps to remove debris, chemical components, and biological impurities that can interfere with microbiological detection. This study aimed to optimize a previously used indirect processing protocol, which included a series of washing and centrifugation steps. Optimization of the protocol included: identifying an ideal extraction diluent, variation in the number of wash steps, variation in the initial centrifugation speed, sonication and shaking mechanisms. The optimized protocol was demonstrated at two laboratories in order to evaluate the recovery of spores from loamy and sandy soils. The new protocol demonstrated an improved limit of detection for loamy and sandy soils over the non-optimized protocol with an approximate matrix limit of detection at 14 spores/g of soil. There were no significant differences overall between the two laboratories for either soil type, suggesting that the processing protocol will be robust enough to use at multiple laboratories while achieving comparable recoveries.

Two-step optimization of pressure and recovery of reverse osmosis desalination process.

PubMed

Liang, Shuang; Liu, Cui; Song, Lianfa

2009-05-01

Driving pressure and recovery are two primary design variables of a reverse osmosis process that largely determine the total cost of seawater and brackish water desalination. A two-step optimization procedure was developed in this paper to determine the values of driving pressure and recovery that minimize the total cost of RO desalination. It was demonstrated that the optimal net driving pressure is solely determined by the electricity price and the membrane price index, which is a lumped parameter to collectively reflect membrane price, resistance, and service time. On the other hand, the optimal recovery is determined by the electricity price, initial osmotic pressure, and costs for pretreatment of raw water and handling of retentate. Concise equations were derived for the optimal net driving pressure and recovery. The dependences of the optimal net driving pressure and recovery on the electricity price, membrane price, and costs for raw water pretreatment and retentate handling were discussed.

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

PubMed

Barbagallo, Simone; Corradi, Luca; de Ville de Goyet, Jean; Iannucci, Marina; Porro, Ivan; Rosso, Nicola; Tanfani, Elena; Testi, Angela

2015-05-17

The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of

Enzymatic process optimization for the in vitro production of isoprene from mevalonate.

PubMed

Cheng, Tao; Liu, Hui; Zou, Huibin; Chen, Ningning; Shi, Mengxun; Xie, Congxia; Zhao, Guang; Xian, Mo

2017-01-09

As an important bulk chemical for synthetic rubber, isoprene can be biosynthesized by robust microbes. But rational engineering and optimization are often demanded to make the in vivo process feasible due to the complexities of cellular metabolism. Alternative synthetic biochemistry strategies are in fast development to produce isoprene or isoprenoids in vitro. This study set up an in vitro enzyme synthetic chemistry process using 5 enzymes in the lower mevalonate pathway to produce isoprene from mevalonate. We found the level and ratio of individual enzymes would significantly affect the efficiency of the whole system. The optimized process using 10 balanced enzyme unites (5.0 µM of MVK, PMK, MVD; 10.0 µM of IDI, 80.0 µM of ISPS) could produce 6323.5 µmol/L/h (430 mg/L/h) isoprene in a 2 ml in vitro system. In a scale up process (50 ml) only using 1 balanced enzyme unit (0.5 µM of MVK, PMK, MVD; 1.0 µM of IDI, 8.0 µM of ISPS), the system could produce 302 mg/L isoprene in 40 h, which showed higher production rate and longer reaction phase with comparison of the in vivo control. By optimizing the enzyme levels of lower MVA pathway, synthetic biochemistry methods could be set up for the enzymatic production of isoprene or isoprenoids from mevalonate.

Processing Optimization of Deformed Plain Woven Thermoplastic Composites

NASA Astrophysics Data System (ADS)

Smith, John R.; Vaidya, Uday K.

2013-12-01

This research addresses the processing optimization of post-manufactured, plain weave architecture composite panels consisted of four glass layers and thermoplastic polyurethane (TPU) when formed with only localized heating. Often times, during the production of deep drawn composite parts, a fabric preform experiences various defects, including non-isothermal heating and thickness variations. Minimizing these defects is of utmost importance for mass produceability in a practical manufacturing process. The broad objective of this research was to implement a design of experiments approach to minimize through-thickness composite panel variation during manufacturing by varying the heating time, the temperature of heated components and the clamping pressure. It was concluded that the heated tooling with least area contact was most influential, followed by the length of heating time and the amount of clamping pressure.

Aircraft Flight Modeling During the Optimization of Gas Turbine Engine Working Process

NASA Astrophysics Data System (ADS)

Tkachenko, A. Yu; Kuz'michev, V. S.; Krupenich, I. N.

2018-01-01

The article describes a method for simulating the flight of the aircraft along a predetermined path, establishing a functional connection between the parameters of the working process of gas turbine engine and the efficiency criteria of the aircraft. This connection is necessary for solving the optimization tasks of the conceptual design stage of the engine according to the systems approach. Engine thrust level, in turn, influences the operation of aircraft, thus making accurate simulation of the aircraft behavior during flight necessary for obtaining the correct solution. The described mathematical model of aircraft flight provides the functional connection between the airframe characteristics, working process of gas turbine engines (propulsion system), ambient and flight conditions and flight profile features. This model provides accurate results of flight simulation and the resulting aircraft efficiency criteria, required for optimization of working process and control function of a gas turbine engine.

Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

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, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.

Evaluation of Advanced Thermal Protection Techniques for Future Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Olds, John R.; Cowart, Kris

2001-01-01

A method for integrating Aeroheating analysis into conceptual reusable launch vehicle RLV design is presented in this thesis. This process allows for faster turn-around time to converge a RLV design through the advent of designing an optimized thermal protection system (TPS). It consists of the coupling and automation of four computer software packages: MINIVER, TPSX, TCAT and ADS. MINIVER is an Aeroheating code that produces centerline radiation equilibrium temperatures, convective heating rates, and heat loads over simplified vehicle geometries. These include flat plates and swept cylinders that model wings and leading edges, respectively. TPSX is a NASA Ames material properties database that is available on the World Wide Web. The newly developed Thermal Calculation Analysis Tool (TCAT) uses finite difference methods to carry out a transient in-depth I-D conduction analysis over the center mold line of the vehicle. This is used along with the Automated Design Synthesis (ADS) code to correctly size the vehicle's thermal protection system JPS). The numerical optimizer ADS uses algorithms that solve constrained and unconstrained design problems. The resulting outputs for this process are TPS material types, unit thicknesses, and acreage percentages. TCAT was developed for several purposes. First, it provides a means to calculate the transient in-depth conduction seen by the surface of the TPS material that protects a vehicle during ascent and reentry. Along with the in-depth conduction, radiation from the surface of the material is calculated along with the temperatures at the backface and interior parts of the TPS material. Secondly, TCAT contributes added speed and automation to the overall design process. Another motivation in the development of TCAT is optimization.

Crash pulse optimization for occupant protection at various impact velocities.

PubMed

Ito, Daisuke; Yokoi, Yusuke; Mizuno, Koji

2015-01-01

Vehicle deceleration has a large influence on occupant kinematic behavior and injury risks in crashes, and the optimization of the vehicle crash pulse that mitigates occupant loadings has been the subject of substantial research. These optimization research efforts focused on only high-velocity impact in regulatory or new car assessment programs though vehicle collisions occur over a wide range of velocities. In this study, the vehicle crash pulse was optimized for various velocities with a genetic algorithm. Vehicle deceleration was optimized in a full-frontal rigid barrier crash with a simple spring-mass model that represents the vehicle-occupant interaction and a Hybrid III 50th percentile male multibody model. To examine whether the vehicle crash pulse optimized at the high impact velocity is useful for reducing occupant loading at all impact velocities less than the optimized velocity, the occupant deceleration was calculated at various velocities for the optimized crash pulse determined at a high speed. The optimized vehicle deceleration-deformation characteristics that are effective for various velocities were investigated with 2 approaches. The optimized vehicle crash pulse at a single impact velocity consists of a high initial impulse followed by zero deceleration and then constant deceleration in the final stage. The vehicle deceleration optimized with the Hybrid III model was comparable to that determined from the spring-mass model. The optimized vehicle deceleration-deformation characteristics determined at a high speed did not necessarily lead to an occupant deceleration reduction at a lower velocity. The maximum occupant deceleration at each velocity was normalized by the maximum deceleration determined in the single impact velocity optimization. The resulting vehicle deceleration-deformation characteristic was a square crash pulse. The objective function was defined as the number of injuries, which was the product of the number of collisions at the

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.

IEC 61511 and the capital project process--a protective management system approach.

PubMed

Summers, Angela E

2006-03-17

This year, the process industry has reached an important milestone in process safety-the acceptance of an internationally recognized standard for safety instrumented systems (SIS). This standard, IEC 61511, documents good engineering practice for the assessment, design, operation, maintenance, and management of SISs. The foundation of the standard is established by several requirements in Part 1, Clauses 5-7, which cover the development of a management system aimed at ensuring that functional safety is achieved. The management system includes a quality assurance process for the entire SIS lifecycle, requiring the development of procedures, identification of resources and acquisition of tools. For maximum benefit, the deliverables and quality control checks required by the standard should be integrated into the capital project process, addressing safety, environmental, plant productivity, and asset protection. Industry has become inundated with a multitude of programs focusing on safety, quality, and cost performance. This paper introduces a protective management system, which builds upon the work process identified in IEC 61511. Typical capital project phases are integrated with the management system to yield one comprehensive program to efficiently manage process risk. Finally, the paper highlights areas where internal practices or guidelines should be developed to improve program performance and cost effectiveness.

Modeling and optimization of red currants vacuum drying process by response surface methodology (RSM).

PubMed

Šumić, Zdravko; Vakula, Anita; Tepić, Aleksandra; Čakarević, Jelena; Vitas, Jasmina; Pavlić, Branimir

2016-07-15

Fresh red currants were dried by vacuum drying process under different drying conditions. Box-Behnken experimental design with response surface methodology was used for optimization of drying process in terms of physical (moisture content, water activity, total color change, firmness and rehydratation power) and chemical (total phenols, total flavonoids, monomeric anthocyanins and ascorbic acid content and antioxidant activity) properties of dried samples. Temperature (48-78 °C), pressure (30-330 mbar) and drying time (8-16 h) were investigated as independent variables. Experimental results were fitted to a second-order polynomial model where regression analysis and analysis of variance were used to determine model fitness and optimal drying conditions. The optimal conditions of simultaneously optimized responses were temperature of 70.2 °C, pressure of 39 mbar and drying time of 8 h. It could be concluded that vacuum drying provides samples with good physico-chemical properties, similar to lyophilized sample and better than conventionally dried sample. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal condition for fabricating superhydrophobic Aluminum surfaces with controlled anodizing processes

NASA Astrophysics Data System (ADS)

Saffari, Hamid; Sohrabi, Beheshteh; Noori, Mohammad Reza; Bahrami, Hamid Reza Talesh

2018-03-01

A single step anodizing process is used to produce micro-nano structures on Aluminum (1050) substrates with sulfuric acid as electrolyte. Therefore, surface energy of the anodized layer is reduced using stearic acid modification. Undoubtedly, effects of different parameters including anodizing time, electrical current, and type and concentration of electrolyte on the final contact angle are systemically studied and optimized. Results show that anodizing current of 0.41 A, electrolyte (sulfuric acid) concentration of 15 wt.% and anodizing time of 90 min are optimal conditions which give contact angle as high as 159.2° and sliding angle lower than 5°. Moreover, the study reveals that adding oxalic acid to the sulfuric acid cannot enhance superhydrophobicity of the samples. Also, scanning electron microscopy images of samples show that irregular (bird's nest) structures present on the surface instead of high-ordered honeycomb structures expecting from normal anodizing process. Additionally, X-ray diffraction analysis of the samples shows that only amorphous structures present on the surface. The Brunauer-Emmett-Teller (BET) specific surface area of the anodized layer is 2.55 m2 g-1 in optimal condition. Ultimately, the surface keeps its hydrophobicity in air and deionized water (DIW) after one week and 12 weeks, respectively.

Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo

2017-08-01

This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.

Development of Pangasius steaks by improved sous-vide technology and its process optimization.

PubMed

Kumari, Namita; Singh, Chongtham Baru; Kumar, Raushan; Martin Xavier, K A; Lekshmi, Manjusha; Venkateshwarlu, Gudipati; Balange, Amjad K

2016-11-01

The present study embarked on the objective of optimizing improved sous - vide processing condition for development of ready-to-cook Pangasius steaks with extended shelf-life using response surface methodology. For the development of improved sous - vide cooked product, Pangasius steaks were treated with additional hurdles in various combinations for optimization. Based on the study, suitable combination of chitosan and spices was selected which enhanced antimicrobial and oxidative stability of the product. The Box-Behnken experimental design with 15 trials per model was adopted for designing the experiment to know the effect of independent variables, namely chitosan concentration (X 1 ), cooking time (X 2 ) and cooking temperature (X 3 ) on dependent variable i.e. TBARS value (Y 1 ). From RSM generated model, the optimum condition for sous - vide processing of Pangasius steaks were 1.08% chitosan concentration, 70.93 °C of cooking temperature and 16.48 min for cooking time and predicted minimum value of multiple response optimal condition was Y = 0.855 mg MDA/Kg of fish. The high correlation coefficient (R 2  = 0.975) between the model and the experimental data showed that the model was able to efficiently predict processing condition for development of sous - vide processed Pangasius steaks. This research may help the processing industries and Pangasius fish farmer as it provides an alternative low cost technology for the proper utilization of Pangasius .

Managing the Public Sector Research and Development Portfolio Selection Process: A Case Study of Quantitative Selection and Optimization

DTIC Science & Technology

2016-09-01

PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION by Jason A. Schwartz...PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION 5. FUNDING NUMBERS 6...describing how public sector organizations can implement a research and development (R&D) portfolio optimization strategy to maximize the cost

On optimal designs of transparent WDM networks with 1 + 1 protection leveraged by all-optical XOR network coding schemes

NASA Astrophysics Data System (ADS)

Dao, Thanh Hai

2018-01-01

Network coding techniques are seen as the new dimension to improve the network performances thanks to the capability of utilizing network resources more efficiently. Indeed, the application of network coding to the realm of failure recovery in optical networks has been marking a major departure from traditional protection schemes as it could potentially achieve both rapid recovery and capacity improvement, challenging the prevailing wisdom of trading capacity efficiency for speed recovery and vice versa. In this context, the maturing of all-optical XOR technologies appears as a good match to the necessity of a more efficient protection in transparent optical networks. In addressing this opportunity, we propose to use a practical all-optical XOR network coding to leverage the conventional 1 + 1 optical path protection in transparent WDM optical networks. The network coding-assisted protection solution combines protection flows of two demands sharing the same destination node in supportive conditions, paving the way for reducing the backup capacity. A novel mathematical model taking into account the operation of new protection scheme for optimal network designs is formulated as the integer linear programming. Numerical results based on extensive simulations on realistic topologies, COST239 and NSFNET networks, are presented to highlight the benefits of our proposal compared to the conventional approach in terms of wavelength resources efficiency and network throughput.

Development of Protective Coatings for Co-Sequestration Processes and Pipelines

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

Bierwagen, Gordon; Huang, Yaping

2011-11-30

The program, entitled Development of Protective Coatings for Co-Sequestration Processes and Pipelines, examined the sensitivity of existing coating systems to supercritical carbon dioxide (SCCO2) exposure and developed new coating system to protect pipelines from their corrosion under SCCO2 exposure. A literature review was also conducted regarding pipeline corrosion sensors to monitor pipes used in handling co-sequestration fluids. Research was to ensure safety and reliability for a pipeline involving transport of SCCO2 from the power plant to the sequestration site to mitigate the greenhouse gas effect. Results showed that one commercial coating and one designed formulation can both be supplied asmore » potential candidates for internal pipeline coating to transport SCCO2.« less

To what extent can ecosystem services motivate protecting biodiversity?

PubMed

Dee, Laura E; De Lara, Michel; Costello, Christopher; Gaines, Steven D

2017-08-01

Society increasingly focuses on managing nature for the services it provides people rather than for the existence of particular species. How much biodiversity protection would result from this modified focus? Although biodiversity contributes to ecosystem services, the details of which species are critical, and whether they will go functionally extinct in the future, are fraught with uncertainty. Explicitly considering this uncertainty, we develop an analytical framework to determine how much biodiversity protection would arise solely from optimising net value from an ecosystem service. Using stochastic dynamic programming, we find that protecting a threshold number of species is optimal, and uncertainty surrounding how biodiversity produces services makes it optimal to protect more species than are presumed critical. We define conditions under which the economically optimal protection strategy is to protect all species, no species, and cases in between. We show how the optimal number of species to protect depends upon different relationships between species and services, including considering multiple services. Our analysis provides simple criteria to evaluate when managing for particular ecosystem services could warrant protecting all species, given uncertainty. Evaluating this criterion with empirical estimates from different ecosystems suggests that optimising some services will be more likely to protect most species than others. © 2017 John Wiley & Sons Ltd/CNRS.

Optimizing Endoscope Reprocessing Resources Via Process Flow Queuing Analysis.

PubMed

Seelen, Mark T; Friend, Tynan H; Levine, Wilton C

2018-05-04

The Massachusetts General Hospital (MGH) is merging its older endoscope processing facilities into a single new facility that will enable high-level disinfection of endoscopes for both the ORs and Endoscopy Suite, leveraging economies of scale for improved patient care and optimal use of resources. Finalized resource planning was necessary for the merging of facilities to optimize staffing and make final equipment selections to support the nearly 33,000 annual endoscopy cases. To accomplish this, we employed operations management methodologies, analyzing the physical process flow of scopes throughout the existing Endoscopy Suite and ORs and mapping the future state capacity of the new reprocessing facility. Further, our analysis required the incorporation of historical case and reprocessing volumes in a multi-server queuing model to identify any potential wait times as a result of the new reprocessing cycle. We also performed sensitivity analysis to understand the impact of future case volume growth. We found that our future-state reprocessing facility, given planned capital expenditures for automated endoscope reprocessors (AERs) and pre-processing sinks, could easily accommodate current scope volume well within the necessary pre-cleaning-to-sink reprocessing time limit recommended by manufacturers. Further, in its current planned state, our model suggested that the future endoscope reprocessing suite at MGH could support an increase in volume of at least 90% over the next several years. Our work suggests that with simple mathematical analysis of historic case data, significant changes to a complex perioperative environment can be made with ease while keeping patient safety as the top priority.

Optimal timing in biological processes

USGS Publications Warehouse

Williams, B.K.; Nichols, J.D.

1984-01-01

A general approach for obtaining solutions to a class of biological optimization problems is provided. The general problem is one of determining the appropriate time to take some action, when the action can be taken only once during some finite time frame. The approach can also be extended to cover a number of other problems involving animal choice (e.g., mate selection, habitat selection). Returns (assumed to index fitness) are treated as random variables with time-specific distributions, and can be either observable or unobservable at the time action is taken. In the case of unobservable returns, the organism is assumed to base decisions on some ancillary variable that is associated with returns. Optimal policies are derived for both situations and their properties are discussed. Various extensions are also considered, including objective functions based on functions of returns other than the mean, nonmonotonic relationships between the observable variable and returns; possible death of the organism before action is taken; and discounting of future returns. A general feature of the optimal solutions for many of these problems is that an organism should be very selective (i.e., should act only when returns or expected returns are relatively high) at the beginning of the time frame and should become less and less selective as time progresses. An example of the application of optimal timing to a problem involving the timing of bird migration is discussed, and a number of other examples for which the approach is applicable are described.

Adjusting process count on demand for petascale global optimization

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

Sosonkina, Masha; Watson, Layne T.; Radcliffe, Nicholas R.

2012-11-23

There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running at the petascale are likely to be memory intensive, which makes thrashing a serious problem for many petascale applications. One way to overcome this challenge is to use a dynamic number of processes, so that the total amount of memory available for the computation can be increased on demand. This paper describes modifications made to the massively parallel global optimization code pVTdirect in order to allow for a dynamic number of processes. In particular, themore » modified version of the code monitors memory use and spawns new processes if the amount of available memory is determined to be insufficient. The primary design challenges are discussed, and performance results are presented and analyzed.« less

Ising Processing Units: Potential and Challenges for Discrete Optimization

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

Coffrin, Carleton James; Nagarajan, Harsha; Bent, Russell Whitford

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, presents new opportunities for hybrid-optimization algorithms that leverage these kinds of specialized hardware. In this work, we propose the idea of an Ising processing unit as a computational abstraction for these emerging tools. Challenges involved in using and bench- marking these devices are presented, and open-source software tools are proposed to address some of these challenges. The proposed benchmarking tools and methodology are demonstrated by conducting a baseline study of established solution methods to a D-Wave 2X adiabatic quantum computer, one examplemore » of a commercially available Ising processing unit.« less

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

PubMed Central

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

An intelligent factory-wide optimal operation system for continuous production process

NASA Astrophysics Data System (ADS)

Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping

2016-03-01

In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.

Allogeneic cell therapy bioprocess economics and optimization: downstream processing decisions.

PubMed

Hassan, Sally; Simaria, Ana S; Varadaraju, Hemanthram; Gupta, Siddharth; Warren, Kim; Farid, Suzanne S

2015-01-01

To develop a decisional tool to identify the most cost effective process flowsheets for allogeneic cell therapies across a range of production scales. A bioprocess economics and optimization tool was built to assess competing cell expansion and downstream processing (DSP) technologies. Tangential flow filtration was generally more cost-effective for the lower cells/lot achieved in planar technologies and fluidized bed centrifugation became the only feasible option for handling large bioreactor outputs. DSP bottlenecks were observed at large commercial lot sizes requiring multiple large bioreactors. The DSP contribution to the cost of goods/dose ranged between 20-55%, and 50-80% for planar and bioreactor flowsheets, respectively. This analysis can facilitate early decision-making during process development.

Rational design and optimization of downstream processes of virus particles for biopharmaceutical applications: current advances.

PubMed

Vicente, Tiago; Mota, José P B; Peixoto, Cristina; Alves, Paula M; Carrondo, Manuel J T

2011-01-01

The advent of advanced therapies in the pharmaceutical industry has moved the spotlight into virus-like particles and viral vectors produced in cell culture holding great promise in a myriad of clinical targets, including cancer prophylaxis and treatment. Even though a couple of cases have reached the clinic, these products have yet to overcome a number of biological and technological challenges before broad utilization. Concerning the manufacturing processes, there is significant research focusing on the optimization of current cell culture systems and, more recently, on developing scalable downstream processes to generate material for pre-clinical and clinical trials. We review the current options for downstream processing of these complex biopharmaceuticals and underline current advances on knowledge-based toolboxes proposed for rational optimization of their processing. Rational tools developed to increase the yet scarce knowledge on the purification processes of complex biologicals are discussed as alternative to empirical, "black-boxed" based strategies classically used for process development. Innovative methodologies based on surface plasmon resonance, dynamic light scattering, scale-down high-throughput screening and mathematical modeling for supporting ion-exchange chromatography show great potential for a more efficient and cost-effective process design, optimization and equipment prototyping. Copyright © 2011 Elsevier Inc. All rights reserved.

Process for the preparation of protected 3-amino-1,2-dihydroxypropane acetal and derivatives thereof

DOEpatents

Hollingsworth, Rawle I.; Wang, Guijun

2000-01-01

A process for producing protected 3-amino-1,2-dihydroxypropane acetal, particularly in chiral forms, for use as an intermediate in the preparation of various 3-carbon compounds which are chiral. In particular, the present invention relates to the process for preparation of 3-amino-1,2-dihydroxypropane isopropylidene acetal. The protected 3-amino-1,2-dihydroxypropane acetal is a key intermediate to the preparation of chiral 3-carbon compounds which in turn are intermediates to various pharmaceuticals.

Multi Response Optimization of Laser Micro Marking Process:A Grey- Fuzzy Approach

NASA Astrophysics Data System (ADS)

Shivakoti, I.; Das, P. P.; Kibria, G.; Pradhan, B. B.; Mustafa, Z.; Ghadai, R. K.

2017-07-01

The selection of optimal parametric combination for efficient machining has always become a challenging issue for the manufacturing researcher. The optimal parametric combination always provides a better machining which improves the productivity, product quality and subsequently reduces the production cost and time. The paper presents the hybrid approach of Grey relational analysis and Fuzzy logic to obtain the optimal parametric combination for better laser beam micro marking on the Gallium Nitride (GaN) work material. The response surface methodology has been implemented for design of experiment considering three parameters with their five levels. The parameter such as current, frequency and scanning speed has been considered and the mark width, mark depth and mark intensity has been considered as the process response.

Optimization of valve opening process for the suppression of impulse exhaust noise

NASA Astrophysics Data System (ADS)

Li, Jingxiang; Zhao, Shengdun

2017-02-01

Impulse exhaust noise generated by the sudden impact of discharging flow of pneumatic systems has significant temporal characteristics including high sound pressure and rapid sound transient. The impulse noise exposures are more hazardous to hearing than the energy equivalent uniform noise exposures. This paper presents a novel approach to suppress the peak sound pressure as a major indicator of impulsiveness of the impulse exhaust noise by an optimization of the opening process of valve. Relationships between exhaust flow and impulse noise are described by thermodynamics and noise generating mechanism. Then an optimized approach by controlling the valve opening process is derived under a constraint of pre-setting exhaust time. A modified servo-direct-driven valve was designed and assembled in a typical pneumatic system for the verification experiments comparing with an original solenoid valve. Experimental results with groups of initial cylinder pressures and pre-setting exhaust times are shown to verify the effects of the proposed optimization. Some indicators of energy-equivalent and impulsiveness are introduced to discuss the effects of the noise suppressions. Relationship between noise reduction and exhaust time delay is also discussed.

Fault tolerance in space-based digital signal processing and switching systems: Protecting up-link processing resources, demultiplexer, demodulator, and decoder

NASA Technical Reports Server (NTRS)

Redinbo, Robert

1994-01-01

Fault tolerance features in the first three major subsystems appearing in the next generation of communications satellites are described. These satellites will contain extensive but efficient high-speed processing and switching capabilities to support the low signal strengths associated with very small aperture terminals. The terminals' numerous data channels are combined through frequency division multiplexing (FDM) on the up-links and are protected individually by forward error-correcting (FEC) binary convolutional codes. The front-end processing resources, demultiplexer, demodulators, and FEC decoders extract all data channels which are then switched individually, multiplexed, and remodulated before retransmission to earth terminals through narrow beam spot antennas. Algorithm based fault tolerance (ABFT) techniques, which relate real number parity values with data flows and operations, are used to protect the data processing operations. The additional checking features utilize resources that can be substituted for normal processing elements when resource reconfiguration is required to replace a failed unit.

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

Optimal control of raw timber production processes

Treesearch

Ivan Kolenka

1978-01-01

This paper demonstrates the possibility of optimal planning and control of timber harvesting activ-ities with mathematical optimization models. The separate phases of timber harvesting are represented by coordinated models which can be used to select the optimal decision for the execution of any given phase. The models form a system whose components are connected and...

Atmospheric Pressure Plasma-Electrospin Hybrid Process for Protective Applications

NASA Astrophysics Data System (ADS)

Vitchuli Gangadharan, Narendiran

2011-12-01

Chemical and biological (C-B) warfare agents like sarin, sulfur mustard, anthrax are usually dispersed into atmosphere in the form of micro aerosols. They are considered to be dangerous weapon of mass destruction next to nuclear weapons. The airtight protective clothing materials currently available are able to stop the diffusion of threat agents but not good enough to detoxify them, which endangers the wearers. Extensive research efforts are being made to prepare advanced protective clothing materials that not only prevent the diffusion of C-B agents, but also detoxify them into harmless products thus ensuring the safety and comfort of the wearer. Electrospun nanofiber mats are considered to have effective filtration characteristics to stop the diffusion of submicron level particulates without sacrificing air permeability characteristics and could be used in protective application as barrier material. In addition, functional nanofibers could be potentially developed to detoxify the C-B warfare threats into harmless products. In this research, electrospun nanofibers were deposited on fabric surface to improve barrier efficiency without sacrificing comfort-related properties of the fabrics. Multi-functional nanofibers were fabricated through an electrospinning-electrospraying hybrid process and their ability to detoxify simulants of C-B agents was evaluated. Nanofibers were also deposited onto plasma-pretreated woven fabric substrate through a newly developed plasma-electrospinning hybrid process, to improve the adhesive properties of nanofibers on the fabric surface. The nanofiber adhesion and durability properties were evaluated by peel test, flex and abrasion resistance tests. In this research work, following tasks have been carried out: i) Controlled deposition of nanofiber mat onto woven fabric substrate Electrospun Nylon 6 fiber mats were deposited onto woven 50/50 Nylon/Cotton fabric with the motive of making them into protective material against submicron

Optimization of chlorine fluxing process for magnesium removal from molten aluminum

NASA Astrophysics Data System (ADS)

Fu, Qian

High-throughput and low operational cost are the keys to a successful industrial process. Much aluminum is now recycled in the form of used beverage cans and this aluminum is of alloys that contain high levels of magnesium. It is common practice to "demag" the metal by injecting chlorine that preferentially reacts with the magnesium. In the conventional chlorine fluxing processes, low reaction efficiency results in excessive reactive gas emissions. In this study, through an experimental investigation of the reaction kinetics involved in this process, a mathematical model is set up for the purpose of process optimization. A feedback controlled chlorine reduction process strategy is suggested for demagging the molten aluminum to the desired magnesium level without significant gas emissions. This strategy also needs the least modification of the existing process facility. The suggested process time will only be slightly longer than conventional methods and chlorine usage and emissions will be reduced. In order to achieve process optimization through novel designs in any fluxing process, a system is necessary for measuring the bubble distribution in liquid metals. An electro-resistivity probe described in the literature has low accuracy and its capability to measure bubble distribution has not yet been fully demonstrated. A capacitance bubble probe was designed for bubble measurements in molten metals. The probe signal was collected and processed digitally. Higher accuracy was obtained by higher discrimination against corrupted signals. A single-size bubble experiment in Belmont metal was designed to reveal the characteristic response of the capacitance probe. This characteristic response fits well with a theoretical model. It is suggested that using a properly designed deconvolution process, the actual bubble size distribution can be calculated. The capacitance probe was used to study some practical bubble generation devices. Preliminary results on bubble distribution

Grey Relational Analysis Coupled with Principal Component Analysis for Optimization of Stereolithography Process to Enhance Part Quality

NASA Astrophysics Data System (ADS)

Raju, B. S.; Sekhar, U. Chandra; Drakshayani, D. N.

2017-08-01

The paper investigates optimization of stereolithography process for SL5530 epoxy resin material to enhance part quality. The major characteristics indexed for performance selected to evaluate the processes are tensile strength, Flexural strength, Impact strength and Density analysis and corresponding process parameters are Layer thickness, Orientation and Hatch spacing. In this study, the process is intrinsically with multiple parameters tuning so that grey relational analysis which uses grey relational grade as performance index is specially adopted to determine the optimal combination of process parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively desired. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of process parameters. Hence, this confirm that the proposed approach in this study can be an useful tool to improve the process parameters in stereolithography process, which is very useful information for machine designers as well as RP machine users.

Design and optimization of a chromatographic purification process for Streptococcus pneumoniae serotype 23F capsular polysaccharide by a Design of Experiments approach.

PubMed

Ji, Yu; Tian, Yang; Ahnfelt, Mattias; Sui, Lili

2014-06-27

Multivalent pneumococcal vaccines were used worldwide to protect human beings from pneumococcal diseases. In order to eliminate the toxic organic solutions used in the traditional vaccine purification process, an alternative chromatographic process for Streptococcus pneumoniae serotype 23F capsular polysaccharide (CPS) was proposed in this study. The strategy of Design of Experiments (DoE) was introduced into the process development to solve the complicated design procedure. An initial process analysis was given to review the whole flowchart, identify the critical factors of chromatography through FMEA and chose the flowthrough mode due to the property of the feed. A resin screening study was then followed to select candidate resins. DoE was utilized to generate a resolution IV fractional factorial design to further compare candidates and narrow down the design space. After Capto Adhere was selected, the Box-Behnken DoE was executed to model the process and characterize all effects of factors on the responses. Finally, Monte Carlo simulation was used to optimize the process, test the chosen optimal conditions and define the control limit. The results of three scale-up runs at set points verified the DoE and simulation predictions. The final results were well in accordance with the EU pharmacopeia requirements: Protein/CPS (w/w) 1.08%; DNA/CPS (w/w) 0.61%; the phosphorus content 3.1%; the nitrogen 0.315% and the Methyl-pentose percentage 47.9%. Other tests of final pure CPS also met the pharmacopeia specifications. This alternative chromatographic purification process for pneumococcal vaccine without toxic organic solvents was successfully developed by the DoE approach and proved scalability, robustness and suitability for large scale manufacturing. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of grinding of superalloys and ceramics for off-line process optimization

NASA Astrophysics Data System (ADS)

Sathyanarayanan, G.

The present study has compared the performances of resinoid, vitrified, and electroplated CBN wheels in creep feed grinding of M42 and D2 tool steels. Responses such as a specific energy, normal and tangential forces, and surface roughness were used as measures of performance. It was found that creep feed grinding with resinoid, vitrified, and electroplated CBN wheels has its own advantages, but no single wheel could provide good finish, lower specific energy, and high material removal rates simultaneously. To optimize the CBN grinding with different bonded wheels, a Multiple Criteria Decision Making (MCDM) methodology was used. Creep feed grinding of superalloys, Ti-6Al-4V and Inconel 718, has been modeled by utilizing neural networks to optimize the grinding process. A parallel effort was directed at creep feed grinding of alumina ceramics with diamond wheels to investigate the influence of process variables on responses based on experimental results and statistical analysis. The conflicting influence of variables was observed. This led to the formulation of ceramic grinding process as a multi-objective nonlinear mixed integer problem.

A trust-region algorithm for the optimization of PSA processes using reduced-order modeling

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

Agarwal, A.; Biegler, L.; Zitney, S.

2009-01-01

The last few decades have seen a considerable increase in the applications of adsorptive gas separation technologies, such as pressure swing adsorption (PSA); the applications range from bulk separations to trace contaminant removal. PSA processes are based on solid-gas equilibrium and operate under periodic transient conditions [1]. Bed models for these processes are therefore defined by coupled nonlinear partial differential and algebraic equations (PDAEs) distributed in space and time with periodic boundary conditions that connect the processing steps together and high nonlinearities arising from non-isothermal effects and nonlinear adsorption isotherms. As a result, the optimization of such systems for eithermore » design or operation represents a significant computational challenge to current nonlinear programming algorithms. Model reduction is a powerful methodology that permits systematic generation of cost-efficient low-order representations of large-scale systems that result from discretization of such PDAEs. In particular, low-dimensional approximations can be obtained from reduced order modeling (ROM) techniques based on proper orthogonal decomposition (POD) and can be used as surrogate models in the optimization problems. In this approach, a representative ensemble of solutions of the dynamic PDAE system is constructed by solving a higher-order discretization of the model using the method of lines, followed by the application of Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes). These modes are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDAE system. This approach leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally efficient [2]. The ROM methodology has been successfully applied to a 2-bed 4

Gaussian process regression to accelerate geometry optimizations relying on numerical differentiation

NASA Astrophysics Data System (ADS)

Schmitz, Gunnar; Christiansen, Ove

2018-06-01

We study how with means of Gaussian Process Regression (GPR) geometry optimizations, which rely on numerical gradients, can be accelerated. The GPR interpolates a local potential energy surface on which the structure is optimized. It is found to be efficient to combine results on a low computational level (HF or MP2) with the GPR-calculated gradient of the difference between the low level method and the target method, which is a variant of explicitly correlated Coupled Cluster Singles and Doubles with perturbative Triples correction CCSD(F12*)(T) in this study. Overall convergence is achieved if both the potential and the geometry are converged. Compared to numerical gradient-based algorithms, the number of required single point calculations is reduced. Although introducing an error due to the interpolation, the optimized structures are sufficiently close to the minimum of the target level of theory meaning that the reference and predicted minimum only vary energetically in the μEh regime.

Heat Exchange in “Human body - Thermal protection - Environment” System

NASA Astrophysics Data System (ADS)

Khromova, I. V.

2017-11-01

This article is devoted to the issues of simulation and calculation of thermal processes in the system called “Human body - Thermal protection - Environment” under low temperature conditions. It considers internal heat sources and convective heat transfer between calculated elements. Overall this is important for the Heat Transfer Theory. The article introduces complex heat transfer calculation method and local thermophysical parameters calculation method in the system called «Human body - Thermal protection - Environment», considering passive and active thermal protections, thermophysical and geometric properties of calculated elements in a wide range of environmental parameters (water, air). It also includes research on the influence that thermal resistance of modern materials, used in special protective clothes development, has on heat transfer in the system “Human body - Thermal protection - Environment”. Analysis of the obtained results allows adding of the computer research data to experiments and optimizing of individual life-support system elements, which are intended to protect human body from exposure to external factors.

Optimization of the laser remelting process for HVOF-sprayed Stellite 6 wear resistant coatings

NASA Astrophysics Data System (ADS)

Ciubotariu, Costel-Relu; Frunzăverde, Doina; Mărginean, Gabriela; Șerban, Viorel-Aurel; Bîrdeanu, Aurel-Valentin

2016-03-01

Cobalt base alloys are used in all industrial areas due to their excellent wear resistance. Several studies have shown that Stellite 6 coatings are suitable not only for protection against sliding wear, but also in case of exposure to impact loading. In this respect, a possible application is the protection of hydropower plant components affected by cavitation. The main problem in connection with Stellite 6 is the deposition procedure of the protective layers, both welding and thermal spraying techniques requesting special measures in order to prevent the brittleness of the coating. In this study, Stellite 6 layers were HVOF thermally sprayed on a martensitic 13-4 stainless steel substrate, as usually used for hydraulic machinery components. In order to improve the microstructure of the HVOF-sprayed coatings and their adhesion to the substrate, laser remelting was applied, using a TRUMPF Laser type HL 124P LCU and different working parameters. The microstructure of the coatings, obtained for various remelting conditions, was evaluated by light microscopy, showing the optimal value of the pulse power, which provided a homogenous Stellite 6 layer with good adhesion to the substrate.

Optimization of image processing algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

A Dynamic Process Model for Optimizing the Hospital Environment Cash-Flow

NASA Astrophysics Data System (ADS)

Pater, Flavius; Rosu, Serban

2011-09-01

In this article is presented a new approach to some fundamental techniques of solving dynamic programming problems with the use of functional equations. We will analyze the problem of minimizing the cost of treatment in a hospital environment. Mathematical modeling of this process leads to an optimal control problem with a finite horizon.

Importance of Adjunct Delivery Techniques to Optimize Deployment Success of Distal Protection Filters During Vein Graft Intervention.

PubMed

Kaliyadan, Antony G; Chawla, Harnish; Fischman, David L; Ruggiero, Nicholas; Gannon, Michael; Walinsky, Paul; Savage, Michael P

2017-02-01

technically difficult with complex SVG disease. Adjunct delivery techniques are important to optimize deployment success of distal protection filters during SVG intervention.

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na

2014-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based on grey-level co-occurrence matrix (GLCM) are adopted to describe the visual characteristics of the flotation froth image. Then the kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the high-dimensional input vector composed by the flotation froth image characteristics and process datum and extracts the nonlinear principal components in order to reduce the ESN dimension and network complex. The ESN soft-sensor model of flotation process is optimized by the GSO algorithm with congestion factor. Simulation results show that the model has better generalization and prediction accuracy to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:24982935

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

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

Feng, W.

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequentialmore » events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d

Employer, use of personal protective equipment, and work safety climate: Latino poultry processing workers.

PubMed

Arcury, Thomas A; Grzywacz, Joseph G; Anderson, Andrea M; Mora, Dana C; Carrillo, Lourdes; Chen, Haiying; Quandt, Sara A

2013-02-01

This analysis describes the work safety climate of Latino poultry processing workers and notes differences by worker personal characteristics and employer; describes the use of common personal protective equipment (PPE) among workers; and examines the associations of work safety climate with use of common PPE. Data are from a cross-sectional study of 403 Latino poultry processing workers in western North Carolina. Work safety climate differed little by personal characteristics, but it did differ consistently by employer. Provision of PPE varied; for example, 27.2% of participants were provide with eye protection at no cost, 57.0% were provided with hand protection at no cost, and 84.7% were provided with protective clothing at no cost. PPE use varied by type. Provision of PPE at no cost was associated with lower work safety climate; this result was counter-intuitive. Consistent use of PPE was associated with higher work safety climate. Work safety climate is important for improving workplace safety for immigrant workers. Research among immigrant workers should document work safety climate for different employers and industries, and delineate how work safety climate affects safety behavior and injuries. Copyright © 2012 Wiley Periodicals, Inc.

Synthesis and Process Optimization of Electrospun PEEK-Sulfonated Nanofibers by Response Surface Methodology.

PubMed

Boaretti, Carlo; Roso, Martina; Lorenzetti, Alessandra; Modesti, Michele

2015-07-07

In this study electrospun nanofibers of partially sulfonated polyether ether ketone have been produced as a preliminary step for a possible development of composite proton exchange membranes for fuel cells. Response surface methodology has been employed for the modelling and optimization of the electrospinning process, using a Box-Behnken design. The investigation, based on a second order polynomial model, has been focused on the analysis of the effect of both process (voltage, tip-to-collector distance, flow rate) and material (sulfonation degree) variables on the mean fiber diameter. The final model has been verified by a series of statistical tests on the residuals and validated by a comparison procedure of samples at different sulfonation degrees, realized according to optimized conditions, for the production of homogeneous thin nanofibers.

Life cycle analysis within pharmaceutical process optimization and intensification: case study of active pharmaceutical ingredient production.

PubMed

Ott, Denise; Kralisch, Dana; Denčić, Ivana; Hessel, Volker; Laribi, Yosra; Perrichon, Philippe D; Berguerand, Charline; Kiwi-Minsker, Lioubov; Loeb, Patrick

2014-12-01

As the demand for new drugs is rising, the pharmaceutical industry faces the quest of shortening development time, and thus, reducing the time to market. Environmental aspects typically still play a minor role within the early phase of process development. Nevertheless, it is highly promising to rethink, redesign, and optimize process strategies as early as possible in active pharmaceutical ingredient (API) process development, rather than later at the stage of already established processes. The study presented herein deals with a holistic life-cycle-based process optimization and intensification of a pharmaceutical production process targeting a low-volume, high-value API. Striving for process intensification by transfer from batch to continuous processing, as well as an alternative catalytic system, different process options are evaluated with regard to their environmental impact to identify bottlenecks and improvement potentials for further process development activities. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Collecting conditions usage metadata to optimize current and future ATLAS software and processing

NASA Astrophysics Data System (ADS)

Rinaldi, L.; Barberis, D.; Formica, A.; Gallas, E. J.; Oda, S.; Rybkin, G.; Verducci, M.; ATLAS Collaboration

2017-10-01

Conditions data (for example: alignment, calibration, data quality) are used extensively in the processing of real and simulated data in ATLAS. The volume and variety of the conditions data needed by different types of processing are quite diverse, so optimizing its access requires a careful understanding of conditions usage patterns. These patterns can be quantified by mining representative log files from each type of processing and gathering detailed information about conditions usage for that type of processing into a central repository.

Uncovering a New Moral Dilemma of Economic Optimization in Biotechnological Processing.

PubMed

Vochozka, Marek; Stehel, Vojtěch; Maroušková, Anna

2017-06-08

The trend of emerging biorefineries is to process the harvest as efficiently as possible and without any waste. From the most valuable phytomass, refined medicines, enzymes, dyes and other special reactants are created. Functional foods, food ingredients, oils, alcohol, solvents, plastics, fillers and a wide variety of other chemical products follow. After being treated with nutrient recovery techniques (for fertilizer production), biofuels or soil improvers are produced from the leftovers. Economic optimization algorithms have confirmed that such complex biorefineries can be financially viable only when a high degree of feedstock concentration is included. Because the plant material is extremely voluminous before processing, the farming intensity of special plants increases in the nearest vicinity of agglomerations where the biorefineries are built for logistical reasons. Interdisciplinary analyses revealed that these optimization measures lead to significantly increased pollen levels in neighbouring urban areas and subsequently an increased risk of allergies, respectively costs to the national health system. A new moral dilemma between the shareholder's profit and public interest was uncovered and subjected to disputation.

Multi-objective optimization of a continuous bio-dissimilation process of glycerol to 1, 3-propanediol.

PubMed

Xu, Gongxian; Liu, Ying; Gao, Qunwang

2016-02-10

This paper deals with multi-objective optimization of continuous bio-dissimilation process of glycerol to 1, 3-propanediol. In order to maximize the production rate of 1, 3-propanediol, maximize the conversion rate of glycerol to 1, 3-propanediol, maximize the conversion rate of glycerol, and minimize the concentration of by-product ethanol, we first propose six new multi-objective optimization models that can simultaneously optimize any two of the four objectives above. Then these multi-objective optimization problems are solved by using the weighted-sum and normal-boundary intersection methods respectively. Both the Pareto filter algorithm and removal criteria are used to remove those non-Pareto optimal points obtained by the normal-boundary intersection method. The results show that the normal-boundary intersection method can successfully obtain the approximate Pareto optimal sets of all the proposed multi-objective optimization problems, while the weighted-sum approach cannot achieve the overall Pareto optimal solutions of some multi-objective problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Design and Optimization of Composite Automotive Hatchback Using Integrated Material-Structure-Process-Performance Method

NASA Astrophysics Data System (ADS)

Yang, Xudong; Sun, Lingyu; Zhang, Cheng; Li, Lijun; Dai, Zongmiao; Xiong, Zhenkai

2018-03-01

The application of polymer composites as a substitution of metal is an effective approach to reduce vehicle weight. However, the final performance of composite structures is determined not only by the material types, structural designs and manufacturing process, but also by their mutual restrict. Hence, an integrated "material-structure-process-performance" method is proposed for the conceptual and detail design of composite components. The material selection is based on the principle of composite mechanics such as rule of mixture for laminate. The design of component geometry, dimension and stacking sequence is determined by parametric modeling and size optimization. The selection of process parameters are based on multi-physical field simulation. The stiffness and modal constraint conditions were obtained from the numerical analysis of metal benchmark under typical load conditions. The optimal design was found by multi-discipline optimization. Finally, the proposed method was validated by an application case of automotive hatchback using carbon fiber reinforced polymer. Compared with the metal benchmark, the weight of composite one reduces 38.8%, simultaneously, its torsion and bending stiffness increases 3.75% and 33.23%, respectively, and the first frequency also increases 44.78%.

Optimal Protective Hypothermia in Arrested Mammalian Hearts

PubMed Central

Villet, Outi M.; Ge, Ming; Sekhar, Laigam N.; Corson, Marshall A.; Tylee, Tracy S.; Fan, Lu-Ping; Yao, Lin; Zhu, Chun; Olson, Aaron K.; Buroker, Norman E.; Xu, Cheng-Su; Anderson, David L.; Soh, Yong-Kian; Wang, Elise; Chen, Shi-Han; Portman, Michael A.

2015-01-01

Many therapeutic hypothermia recommendations have been reported, but the information supporting them is sparse, and reveals a need for the data of target therapeutic hypothermia (TTH) from well-controlled experiments. The core temperature ≤35°C is considered as hypothermia, and 29°C is a cooling injury threshold in pig heart in vivo. Thus, an optimal protective hypothermia (OPH) should be in the range 29–35°C. This study was conducted with a pig cardiopulmonary bypass preparation to decrease the core temperature to 29–35°C range at 20 minutes before and 60 minutes during heart arrest. The left ventricular (LV) developed pressure, maximum of the first derivative of LV (dP/dtmax), cardiac power, heart rate, cardiac output, and myocardial velocity (Vmax) were recorded continuously via an LV pressure catheter and an aortic flow probe. At 20 minutes of off-pump during reperfusion after 60 minutes arrest, 17 hypothermic hearts showed that the recovery of Vmax and dP/dtmax established sigmoid curves that consisted of two plateaus: a good recovery plateau at 29–30.5°C, the function recovered to baseline level (BL) (Vmax=118.4%±3.9% of BL, LV dP/dtmax=120.7%±3.1% of BL, n=6); another poor recovery plateau at 34–35°C (Vmax=60.2%±2.8% of BL, LV dP/dtmax=28.0%±5.9% of BL, p<0.05, n=6; ), which are similar to the four normothermia arrest (37°C) hearts (Vmax=55.9%±4.8% of BL, LV dP/dtmax=24.5%±2.1% of BL, n=4). The 32–32.5°C arrest hearts showed moderate recovery (n=5). A point of inflection (around 30.5–31°C) existed at the edge of a good recovery plateau followed by a steep slope. The point presented an OPH that should be the TTH. The results are concordant with data in the mammalian hearts, suggesting that the TTH should be initiated to cool core temperature at 31°C. PMID:25514569

Optimized Enhanced Bioremediation Through 4D Geophysical Monitoring and Autonomous Data Collection, Processing and Analysis

DTIC Science & Technology

2014-09-01

ER-200717) Optimized Enhanced Bioremediation Through 4D Geophysical Monitoring and Autonomous Data Collection, Processing and Analysis...N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Optimized Enhanced Bioremediation Through 4D Geophysical Monitoring and Autonomous Data...8 2.1.2 The Geophysical Signatures of Bioremediation ......................................... 8 2.2 PRIOR

Optimization of tetanus toxoid ammonium sulfate precipitation process using response surface methodology.

PubMed

Brgles, Marija; Prebeg, Pero; Kurtović, Tihana; Ranić, Jelena; Marchetti-Deschmann, Martina; Allmaier, Günter; Halassy, Beata

2016-10-02

Tetanus toxoid (TTd) is a highly immunogenic, detoxified form of tetanus toxin, a causative agent of tetanus disease, produced by Clostridium tetani. Since tetanus disease cannot be eradicated but is easily prevented by vaccination, the need for the tetanus vaccine is permanent. The aim of this work was to investigate the possibility of optimizing TTd purification, i.e., ammonium sulfate precipitation process. The influence of the percentage of ammonium sulfate, starting amount of TTd, buffer type, pH, temperature, and starting purity of TTd on the purification process were investigated using optimal design for response surface models. Responses measured for evaluation of the ammonium sulfate precipitation process were TTd amount (Lf/mL) and total protein content. These two parameters were used to calculate purity (Lf/mgPN) and the yield of the process. Results indicate that citrate buffer, lower temperature, and lower starting amount of TTd result in higher purities of precipitates. Gel electrophoresis combined with matrix-assisted laser desorption ionization-mass spectrometric analysis of precipitates revealed that there are no inter-protein cross-links and that all contaminating proteins have pIs similar to TTd, so this is most probably the reason for the limited success of purification by precipitation.

Ethanol production from banana peels using statistically optimized simultaneous saccharification and fermentation process.

PubMed

Oberoi, Harinder Singh; Vadlani, Praveen V; Saida, Lavudi; Bansal, Sunil; Hughes, Joshua D

2011-07-01

Dried and ground banana peel biomass (BP) after hydrothermal sterilization pretreatment was used for ethanol production using simultaneous saccharification and fermentation (SSF). Central composite design (CCD) was used to optimize concentrations of cellulase and pectinase, temperature and time for ethanol production from BP using SSF. Analysis of variance showed a high coefficient of determination (R(2)) value of 0.92 for ethanol production. On the basis of model graphs and numerical optimization, the validation was done in a laboratory batch fermenter with cellulase, pectinase, temperature and time of nine cellulase filter paper unit/gram cellulose (FPU/g-cellulose), 72 international units/gram pectin (IU/g-pectin), 37 °C and 15 h, respectively. The experiment using optimized parameters in batch fermenter not only resulted in higher ethanol concentration than the one predicted by the model equation, but also saved fermentation time. This study demonstrated that both hydrothermal pretreatment and SSF could be successfully carried out in a single vessel, and use of optimized process parameters helped achieve significant ethanol productivity, indicating commercial potential for the process. To the best of our knowledge, ethanol concentration and ethanol productivity of 28.2 g/l and 2.3 g/l/h, respectively from banana peels have not been reported to date. Copyright © 2011 Elsevier Ltd. All rights reserved.

Encapsulation of natural ingredient for skin protection via nanoemulsion process

NASA Astrophysics Data System (ADS)

Asmatulu, Eylem; Usta, Aybala; Alzahrani, Naif; Patil, Vinay; Vanderwall, Adeesha

2017-04-01

Many of the sunscreens are used during the hot summer time to protect the skin surface. However, some of ingredients in the sunscreens, such as oxybenzone, retinyl palmitate and synthetic fragrances including parabens, phthalates and synthetic musk may disrupt the cells on the skin and create harmful effects to human body. Natural oils may be considered for substitution of harmful ingredients in sunscreens. Many natural oils (e.g., macadamia oil, sesame oil, almond oil and olive oil) have UV protective property and on top of that they have natural essences. Among the natural oils, olive oil has a long history of being used as a home remedy for skincare. Olive oil is used or substituted for cleanser, moisturizer, antibacterial agent and massage reliever for muscle fatigue. It is known that sun protection factor (SPF) of olive oil is around eight. There has been relatively little scientific work performed on the effect of olive oil on the skin as sunscreen. With nanoencapsulation technique, UV light protection of the olive oil can be extended which will provide better coverage for the skin throughout the day. In the present study, natural olive oil was incorporated with DI water and surfactant (sodium dodecyl sulfate - SDS) and sonicated using probe sonicators. Sonication time, and concentrations of olive oil, DI water and surfactant were investigated in detail. The produced nanoemulsions were characterized using dynamic light scattering, and UV-Vis spectroscopy. It is believed that the nanoencupsulation of olive oil could provide better skin protection by slow releasing and deeper penetration of the nanoemulsion on skin surface. Undergraduate engineering students were involved in the project and observed all the process during the laboratory studies, as well as data collection, analysis and presentation. This experience based learning will likely enhance the students' skills and interest in the scientific and engineering studies.

Optimization of startup and shutdown operation of simulated moving bed chromatographic processes.

PubMed

Li, Suzhou; Kawajiri, Yoshiaki; Raisch, Jörg; Seidel-Morgenstern, Andreas

2011-06-24

This paper presents new multistage optimal startup and shutdown strategies for simulated moving bed (SMB) chromatographic processes. The proposed concept allows to adjust transient operating conditions stage-wise, and provides capability to improve transient performance and to fulfill product quality specifications simultaneously. A specially tailored decomposition algorithm is developed to ensure computational tractability of the resulting dynamic optimization problems. By examining the transient operation of a literature separation example characterized by nonlinear competitive isotherm, the feasibility of the solution approach is demonstrated, and the performance of the conventional and multistage optimal transient regimes is evaluated systematically. The quantitative results clearly show that the optimal operating policies not only allow to significantly reduce both duration of the transient phase and desorbent consumption, but also enable on-spec production even during startup and shutdown periods. With the aid of the developed transient procedures, short-term separation campaigns with small batch sizes can be performed more flexibly and efficiently by SMB chromatography. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

NASA Astrophysics Data System (ADS)

Laakso, Petri; Riipinen, Tuomas; Laukkanen, Anssi; Andersson, Tom; Jokinen, Antero; Revuelta, Alejandro; Ruusuvuori, Kimmo

This paper demonstrates the successful printing and optimization of processing parameters of high-strength H13 tool steel by Selective Laser Melting (SLM). D-Optimal Design of Experiments (DOE) approach is used for parameter optimization of laser power, scanning speed and hatch width. With 50 test samples (1×1×1cm) we establish parameter windows for these three parameters in relation to part density. The calculated numerical model is found to be in good agreement with the density data obtained from the samples using image analysis. A thermomechanical finite element simulation model is constructed of the SLM process and validated by comparing the calculated densities retrieved from the model with the experimentally determined densities. With the simulation tool one can explore the effect of different parameters on density before making any printed samples. Establishing a parameter window provides the user with freedom for parameter selection such as choosing parameters that result in fastest print speed.

Combined optimization of image-gathering and image-processing systems for scene feature detection

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

1987-01-01

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

A Fully Coupled Simulation and Optimization Scheme for the Design of 3D Powder Injection Molding Processes

NASA Astrophysics Data System (ADS)

Ayad, G.; Song, J.; Barriere, T.; Liu, B.; Gelin, J. C.

2007-05-01

The paper is concerned with optimization and parametric identification of Powder Injection Molding process that consists first in injection of powder mixture with polymer binder and then to the sintering of the resulting powders parts by solid state diffusion. In the first part, one describes an original methodology to optimize the injection stage based on the combination of Design Of Experiments and an adaptive Response Surface Modeling. Then the second part of the paper describes the identification strategy that one proposes for the sintering stage, using the identification of sintering parameters from dilatometer curves followed by the optimization of the sintering process. The proposed approaches are applied to the optimization for manufacturing of a ceramic femoral implant. One demonstrates that the proposed approach give satisfactory results.

Lunar Habitat Optimization Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

SanScoucie, M. P.; Hull, P. V.; Tinker, M. L.; Dozier, G. V.

2007-01-01

Long-duration surface missions to the Moon and Mars will require bases to accommodate habitats for the astronauts. Transporting the materials and equipment required to build the necessary habitats is costly and difficult. The materials chosen for the habitat walls play a direct role in protection against each of the mentioned hazards. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. Clearly, an optimization method is warranted for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces; therefore, a habitat wall design tool utilizing genetic algorithms (GAs) has been developed. GAs use a "survival of the fittest" philosophy where the most fit individuals are more likely to survive and reproduce. This habitat design optimization tool is a multiobjective formulation of up-mass, heat loss, structural analysis, meteoroid impact protection, and radiation protection. This Technical Publication presents the research and development of this tool as well as a technique for finding the optimal GA search parameters.

Synthesis and Process Optimization of Electrospun PEEK-Sulfonated Nanofibers by Response Surface Methodology

PubMed Central

Boaretti, Carlo; Roso, Martina; Lorenzetti, Alessandra; Modesti, Michele

2015-01-01

In this study electrospun nanofibers of partially sulfonated polyether ether ketone have been produced as a preliminary step for a possible development of composite proton exchange membranes for fuel cells. Response surface methodology has been employed for the modelling and optimization of the electrospinning process, using a Box-Behnken design. The investigation, based on a second order polynomial model, has been focused on the analysis of the effect of both process (voltage, tip-to-collector distance, flow rate) and material (sulfonation degree) variables on the mean fiber diameter. The final model has been verified by a series of statistical tests on the residuals and validated by a comparison procedure of samples at different sulfonation degrees, realized according to optimized conditions, for the production of homogeneous thin nanofibers. PMID:28793427

Fuzzy multi-objective optimization case study based on an anaerobic co-digestion process of food waste leachate and piggery wastewater.

PubMed

Choi, Angelo Earvin Sy; Park, Hung Suck

2018-06-20

This paper presents the development and evaluation of fuzzy multi-objective optimization for decision-making that includes the process optimization of anaerobic digestion (AD) process. The operating cost criteria which is a fundamental research gap in previous AD analysis was integrated for the case study in this research. In this study, the mixing ratio of food waste leachate (FWL) and piggery wastewater (PWW), calcium carbonate (CaCO 3 ) and sodium chloride (NaCl) concentrations were optimized to enhance methane production while minimizing operating cost. The results indicated a maximum of 63.3% satisfaction for both methane production and operating cost under the following optimal conditions: mixing ratio (FWL: PWW) - 1.4, CaCO 3 - 2970.5 mg/L and NaCl - 2.7 g/L. In multi-objective optimization, the specific methane yield (SMY) was 239.0 mL CH 4 /g VS added , while 41.2% volatile solids reduction (VSR) was obtained at an operating cost of 56.9 US$/ton. In comparison with the previous optimization study that utilized the response surface methodology, the SMY, VSR and operating cost of the AD process were 310 mL/g, 54% and 83.2 US$/ton, respectively. The results from multi-objective fuzzy optimization proves to show the potential application of this technique for practical decision-making in the process optimization of AD process. Copyright © 2018 Elsevier Ltd. All rights reserved.

An Assessment of Decision-Making Processes: Evaluation of Where Land Protection Planning Can Incorporate Climate Change Information (Final Report)

EPA Science Inventory

EPA announced the availability of the final report, An Assessment of Decision-Making Processes: Evaluation of Where Land Protection Planning Can Incorporate Climate Change Information. This report is a review of decision-making processes of selected land protection prog...

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Surgical Informed Consent Process in Neurosurgery

PubMed Central

Park, Jaechan; Park, Hyojin

2017-01-01

The doctrine of informed consent, as opposed to medical paternalism, is intended to facilitate patient autonomy by allowing patient participation in the medical decision-making process. However, regrettably, the surgical informed consent (SIC) process is invariably underestimated and reduced to a documentary procedure to protect physicians from legal liability. Moreover, residents are rarely trained in the clinical and communicative skills required for the SIC process. Accordingly, to increase professional awareness of the SIC process, a brief history and introduction to the current elements of SIC, the obstacles to patient autonomy and SIC, benefits and drawbacks of SIC, planning of an optimal SIC process, and its application to cases of an unruptured intracranial aneurysm are all presented. Optimal informed consent process can provide patients with a good comprehension of their disease and treatment, augmented autonomy, a strong therapeutic alliance with their doctors, and psychological defenses for coping with stressful surgical circumstances. PMID:28689386

Ethanol production from sweet sorghum bagasse through process optimization using response surface methodology.

PubMed

Lavudi, Saida; Oberoi, Harinder Singh; Mangamoori, Lakshmi Narasu

2017-08-01

In this study, comparative evaluation of acid- and alkali pretreatment of sweet sorghum bagasse (SSB) was carried out for sugar production after enzymatic hydrolysis. Results indicated that enzymatic hydrolysis of alkali-pretreated SSB resulted in higher production of glucose, xylose and arabinose, compared to the other alkali concentrations and also acid-pretreated biomass. Response Surface Methodology (RSM) was, therefore, used to optimize parameters, such as alkali concentration, temperature and time of pretreatment prior to enzymatic hydrolysis to maximize the production of sugars. The independent variables used during RSM included alkali concentration (1.5-4%), pretreatment temperature (125-140 °C) and pretreatment time (10-30 min) were investigated. Process optimization resulted in glucose and xylose concentration of 57.24 and 10.14 g/L, respectively. Subsequently, second stage optimization was conducted using RSM for optimizing parameters for enzymatic hydrolysis, which included substrate concentration (10-15%), incubation time (24-60 h), incubation temperature (40-60 °C) and Celluclast concentration (10-20 IU/g-dwt). Substrate concentration 15%, (w/v) temperature of 60 °C, Celluclast concentration of 20 IU/g-dwt and incubation time of 58 h led to a glucose concentration of 68.58 g/l. Finally, simultaneous saccharification fermentation (SSF) as well as separated hydrolysis and fermentation (SHF) was evaluated using Pichia kudriavzevii HOP-1 for production of ethanol. Significant difference in ethanol concentration was not found using either SSF or SHF; however, ethanol productivity was higher in case of SSF, compared to SHF. This study has established a platform for conducting scale-up studies using the optimized process parameters.

Vulnerability and Protection Talk: Systemic Therapy Process with People with Intellectual Disability

ERIC Educational Resources Information Center

Pote, Helen; Mazon, Teresa; Clegg, Jennifer; King, Susan

2011-01-01

Background: Vulnerability and protection are key concepts within the literature relating to systemic therapy for people with an intellectual disability (ID). This paper explores the processes by which these concepts were discussed in systemic therapy sessions. Method: Four videotapes of systemic therapy sessions were evaluated using a qualitative…

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints.

PubMed

Tchamna, Rodrigue; Lee, Moonyong

2018-01-01

This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process

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

Ho, Chao Chung, E-mail: ho919@pchome.com.tw

Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This ismore » because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms.« less

Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process.

PubMed

Ho, Chao Chung

2011-07-01

Ever since Taiwan's National Health Insurance implemented the diagnosis-related groups payment system in January 2010, hospital income has declined. Therefore, to meet their medical waste disposal needs, hospitals seek suppliers that provide high-quality services at a low cost. The enactment of the Waste Disposal Act in 1974 had facilitated some improvement in the management of waste disposal. However, since the implementation of the National Health Insurance program, the amount of medical waste from disposable medical products has been increasing. Further, of all the hazardous waste types, the amount of infectious medical waste has increased at the fastest rate. This is because of the increase in the number of items considered as infectious waste by the Environmental Protection Administration. The present study used two important findings from previous studies to determine the critical evaluation criteria for selecting infectious medical waste disposal firms. It employed the fuzzy analytic hierarchy process to set the objective weights of the evaluation criteria and select the optimal infectious medical waste disposal firm through calculation and sorting. The aim was to propose a method of evaluation with which medical and health care institutions could objectively and systematically choose appropriate infectious medical waste disposal firms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Optimality of the barrier strategy in de Finetti's dividend problem for spectrally negative Lévy processes: An alternative approach

NASA Astrophysics Data System (ADS)

Yin, Chuancun; Wang, Chunwei

2009-11-01

The optimal dividend problem proposed in de Finetti [1] is to find the dividend-payment strategy that maximizes the expected discounted value of dividends which are paid to the shareholders until the company is ruined. Avram et al. [9] studied the case when the risk process is modelled by a general spectrally negative Lévy process and Loeffen [10] gave sufficient conditions under which the optimal strategy is of the barrier type. Recently Kyprianou et al. [11] strengthened the result of Loeffen [10] which established a larger class of Lévy processes for which the barrier strategy is optimal among all admissible ones. In this paper we use an analytical argument to re-investigate the optimality of barrier dividend strategies considered in the three recent papers.

Nitrogen removal process optimization in New York City WPCPS: a case study of Wards Island WPCP.

PubMed

Ramalingam, K; Fillos, J; Musabyimana, M; Deur, A; Beckmann, K

2009-01-01

The New York City Department of Environmental Protection has been engaged in a continuous process to develop a nitrogen removal program to reduce the nitrogen mass discharge from its water pollution control plants, (WPCPs), from 49,158 kg/d to 20,105 kg/d by the year 2017 as recommended by the Long Island Sound Study. As part of the process, a comprehensive research effort was undertaken involving bench, pilot and full scale studies to identify the most effective way to upgrade and optimize the existing WPCPs. Aeration tank 13 (AT-13) at the Wards Island WPCP was particularly attractive as a full-scale research facility because its aeration tank with its dedicated final settling tanks and RAS pumps could be isolated from the remaining treatment facilities. The nitrogen removal performance of AT-13, which, at the time, was operated as a "basic step feed BNR Facility", was evaluated and concurrently nitrification kinetic parameters were measured using in-situ bench scale experiments. Additional bench scale experiments provided denitrification rates using different sources of carbon and measurement of the maximum specific growth rate of nitrifying bacteria. The combined findings were then used to upgrade AT-13 to a "full" BNR facility with carbon and alkalinity addition. This paper will focus on the combined bench and full scale results that were the basis for the consequent upgrade.

Study of Research and Development Processes through Fuzzy Super FRM Model and Optimization Solutions

PubMed Central

Sârbu, Flavius Aurelian; Moga, Monika; Calefariu, Gavrilă; Boșcoianu, Mircea

2015-01-01

The aim of this study is to measure resources for R&D (research and development) at the regional level in Romania and also obtain primary data that will be important in making the right decisions to increase competitiveness and development based on an economic knowledge. As our motivation, we would like to emphasize that by the use of Super Fuzzy FRM model we want to determine the state of R&D processes at regional level using a mean different from the statistical survey, while by the two optimization methods we mean to provide optimization solutions for the R&D actions of the enterprises. Therefore to fulfill the above mentioned aim in this application-oriented paper we decided to use a questionnaire and for the interpretation of the results the Super Fuzzy FRM model, representing the main novelty of our paper, as this theory provides a formalism based on matrix calculus, which allows processing of large volumes of information and also delivers results difficult or impossible to see, through statistical processing. Furthermore another novelty of the paper represents the optimization solutions submitted in this work, given for the situation when the sales price is variable, and the quantity sold is constant in time and for the reverse situation. PMID:25821846

Optimization of Bioethanol Production Using Whole Plant of Water Hyacinth as Substrate in Simultaneous Saccharification and Fermentation Process

PubMed Central

Zhang, Qiuzhuo; Weng, Chen; Huang, Huiqin; Achal, Varenyam; Wang, Duanchao

2016-01-01

Water hyacinth was used as substrate for bioethanol production in the present study. Combination of acid pretreatment and enzymatic hydrolysis was the most effective process for sugar production that resulted in the production of 402.93 mg reducing sugar at optimal condition. A regression model was built to optimize the fermentation factors according to response surface method in saccharification and fermentation (SSF) process. The optimized condition for ethanol production by SSF process was fermented at 38.87°C in 81.87 h when inoculated with 6.11 ml yeast, where 1.291 g/L bioethanol was produced. Meanwhile, 1.289 g/L ethanol was produced during experimentation, which showed reliability of presented regression model in this research. The optimization method discussed in the present study leading to relatively high bioethanol production could provide a promising way for Alien Invasive Species with high cellulose content. PMID:26779125

The possibility of increasing the efficiency of accessible coal deposits by optimizing dimensions of protective pillars or the scope of exploitation

NASA Astrophysics Data System (ADS)

Bańka, Piotr; Badura, Henryk; Wesołowski, Marek

2017-11-01

One of the ways to protect objects exposed to the influences of mining exploitation is establishing protective pillars for them. Properly determined pillar provides effective protection of the object for which it was established. Determining correct dimensions of a pillar requires taking into account contradictory requirements. Protection measures against the excessive influences of mining exploitation require designing the largest possible pillars, whereas economic requirements suggest a maximum reduction of the size of resources left in the pillar. This paper presents algorithms and programs developed for determining optimal dimensions of protective pillars for surface objects and shafts. The issue of designing a protective pillar was treated as a nonlinear programming task. The objective function are the resources left in a pillar while nonlinear limitations are the deformation values evoked by the mining exploitation. Resources in the pillar may be weighted e.g. by calorific value or by the inverse of output costs. The possibility of designing pillars of any polygon shape was taken into account. Because of the applied exploitation technologies the rectangular pillar shape should be considered more advantageous than the oval one, though it does not ensure the minimization of resources left in a pillar. In this article there is also presented a different approach to the design of protective pillars, which instead of fixing the pillar boundaries in subsequent seams, the length of longwall panels of the designed mining exploitation is limited in a way that ensures the effective protection of an object while maximizing the extraction ratio of the deposit.

Algorithm and Software for Calculating Optimal Regimes of the Process Water Supply System at the Kalininskaya NPP{sup 1}

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

Murav’ev, V. P., E-mail: murval@mail.ru; Kochetkov, A. V.; Glazova, E. G.

An algorithm and software for calculating the optimal operating regimes of the process water supply system at the Kalininskaya NPP are described. The parameters of the optimal regimes are determined for time varying meteorological conditions and condensation loads of the NPP. The optimal flow of the cooling water in the turbines is determined computationally; a regime map with the data on the optimal water consumption distribution between the coolers and displaying the regimes with an admissible heat load on the natural cooling lakes is composed. Optimizing the cooling system for a 4000-MW NPP will make it possible to conserve atmore » least 155,000 MW · h of electricity per year. The procedure developed can be used to optimize the process water supply systems of nuclear and thermal power plants.« less

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.

Optimal performance of single-column chromatography and simulated moving bed processes for the separation of optical isomers

NASA Astrophysics Data System (ADS)

Medi, Bijan; Kazi, Monzure-Khoda; Amanullah, Mohammad

2013-06-01

Chromatography has been established as the method of choice for the separation and purification of optically pure drugs which has a market size of about 250 billion USD. Single column chromatography (SCC) is commonly used in the development and testing phase of drug development while multi-column Simulated Moving Bed (SMB) chromatography is more suitable for large scale production due to its continuous nature. In this study, optimal performance of SCC and SMB processes for the separation of optical isomers under linear and overloaded separation conditions has been investigated. The performance indicators, namely productivity and desorbent requirement have been compared under geometric similarity for the separation of a mixture of guaifenesin, and Tröger's base enantiomers. SCC process has been analyzed under equilibrium assumption i.e., assuming infinite column efficiency, and zero dispersion, and its optimal performance parameters are compared with the optimal prediction of an SMB process by triangle theory. Simulation results obtained using actual experimental data indicate that SCC may compete with SMB in terms of productivity depending on the molecules to be separated. Besides, insights into the process performances in terms of degree of freedom and relationship between the optimal operating point and solubility limit of the optical isomers have been ascertained. This investigation enables appropriate selection of single or multi-column chromatographic processes based on column packing properties and isotherm parameters.

Critical Infrastructure Protection II, The International Federation for Information Processing, Volume 290.

NASA Astrophysics Data System (ADS)

Papa, Mauricio; Shenoi, Sujeet

The information infrastructure -- comprising computers, embedded devices, networks and software systems -- is vital to day-to-day operations in every sector: information and telecommunications, banking and finance, energy, chemicals and hazardous materials, agriculture, food, water, public health, emergency services, transportation, postal and shipping, government and defense. Global business and industry, governments, indeed society itself, cannot function effectively if major components of the critical information infrastructure are degraded, disabled or destroyed. Critical Infrastructure Protection II describes original research results and innovative applications in the interdisciplinary field of critical infrastructure protection. Also, it highlights the importance of weaving science, technology and policy in crafting sophisticated, yet practical, solutions that will help secure information, computer and network assets in the various critical infrastructure sectors. Areas of coverage include: - Themes and Issues - Infrastructure Security - Control Systems Security - Security Strategies - Infrastructure Interdependencies - Infrastructure Modeling and Simulation This book is the second volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.10 on Critical Infrastructure Protection, an international community of scientists, engineers, practitioners and policy makers dedicated to advancing research, development and implementation efforts focused on infrastructure protection. The book contains a selection of twenty edited papers from the Second Annual IFIP WG 11.10 International Conference on Critical Infrastructure Protection held at George Mason University, Arlington, Virginia, USA in the spring of 2008.

Optimization of A(2)O BNR processes using ASM and EAWAG Bio-P models: model performance.

PubMed

El Shorbagy, Walid E; Radif, Nawras N; Droste, Ronald L

2013-12-01

This paper presents the performance of an optimization model for a biological nutrient removal (BNR) system using the anaerobic-anoxic-oxic (A(2)O) process. The formulated model simulates removal of organics, nitrogen, and phosphorus using a reduced International Water Association (IWA) Activated Sludge Model #3 (ASM3) model and a Swiss Federal Institute for Environmental Science and Technology (EAWAG) Bio-P module. Optimal sizing is attained considering capital and operational costs. Process performance is evaluated against the effect of influent conditions, effluent limits, and selected parameters of various optimal solutions with the following results: an increase of influent temperature from 10 degrees C to 25 degrees C decreases the annual cost by about 8.5%, an increase of influent flow from 500 to 2500 m(3)/h triples the annual cost, the A(2)O BNR system is more sensitive to variations in influent ammonia than phosphorus concentration and the maximum growth rate of autotrophic biomass was the most sensitive kinetic parameter in the optimization model.

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

Optimization of the monitoring of landfill gas and leachate in closed methanogenic landfills.

PubMed

Jovanov, Dejan; Vujić, Bogdana; Vujić, Goran

2018-06-15

Monitoring of the gas and leachate parameters in a closed landfill is a long-term activity defined by national legislative worldwide. Serbian Waste Disposal Law defines the monitoring of a landfill at least 30 years after its closing, but the definition of the monitoring extent (number and type of parameters) is incomplete. In order to define and clear all the uncertainties, this research focuses on process of monitoring optimization, using the closed landfill in Zrenjanin, Serbia, as the experimental model. The aim of optimization was to find representative parameters which would define the physical, chemical and biological processes in the closed methanogenic landfill and to make this process less expensive. Research included development of the five monitoring models with different number of gas and leachate parameters and each model has been processed in open source software GeoGebra which is often used for solving optimization problems. The results of optimization process identified the most favorable monitoring model which fulfills all the defined criteria not only from the point of view of mathematical analyses, but also from the point of view of environment protection. The final outcome of this research - the minimal required parameters which should be included in the landfill monitoring are precisely defined. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization Program for Drinking Water Systems

EPA Pesticide Factsheets

The Area-Wide Optimization Program (AWOP) provides tools and approaches for drinking water systems to meet water quality optimization goals and provide an increased – and sustainable – level of public health protection to their consumers.

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Price, D. Marvin

1991-01-01

Spacecraft designers have always been concerned about the effects of meteoroid impacts on mission safety. The engineering solution to this problem has generally been to erect a bumper or shield placed outboard from the spacecraft wall to disrupt/deflect the incoming projectiles. Spacecraft designers have a number of tools at their disposal to aid in the design process. These include hypervelocity impact testing, analytic impact predictors, and hydrodynamic codes. Analytic impact predictors generally provide the best quick-look estimate of design tradeoffs. The most complete way to determine the characteristics of an analytic impact predictor is through optimization of the protective structures design problem formulated with the predictor of interest. Space Station Freedom protective structures design insight is provided through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. Major results are presented.

Optimal deployment of resources for maximizing impact in spreading processes

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

Lokhov, Andrey Y.; Saad, David

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distributionmore » of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.« less

Optimal deployment of resources for maximizing impact in spreading processes

DOE PAGES

Lokhov, Andrey Y.; Saad, David

2017-09-12

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distributionmore » of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.« less

Optimal lot sizing in screening processes with returnable defective items

NASA Astrophysics Data System (ADS)

Vishkaei, Behzad Maleki; Niaki, S. T. A.; Farhangi, Milad; Rashti, Mehdi Ebrahimnezhad Moghadam

2014-07-01

This paper is an extension of Hsu and Hsu (Int J Ind Eng Comput 3(5):939-948, 2012) aiming to determine the optimal order quantity of product batches that contain defective items with percentage nonconforming following a known probability density function. The orders are subject to 100 % screening process at a rate higher than the demand rate. Shortage is backordered, and defective items in each ordering cycle are stored in a warehouse to be returned to the supplier when a new order is received. Although the retailer does not sell defective items at a lower price and only trades perfect items (to avoid loss), a higher holding cost incurs to store defective items. Using the renewal-reward theorem, the optimal order and shortage quantities are determined. Some numerical examples are solved at the end to clarify the applicability of the proposed model and to compare the new policy to an existing one. The results show that the new policy provides better expected profit per time.

Optimal deployment of resources for maximizing impact in spreading processes

PubMed Central

2017-01-01

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. We show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples. PMID:28900013

Research and Development of Heavy Gauge X80 Pipeline Plate Utilizing Optimized Rolling and Cooling Process

NASA Astrophysics Data System (ADS)

Li, Shaopo; Li, Jiading; Ding, Wenhua; Zhang, Hai

This paper reports on the experience with the production of 27/33 mm X80 heavy wall thicknesses, large OD (48") in Shouqin Steel Co., Ltd. (SQS). Considering the technology capability of the plate mill in SQS, a optimized rolling and cooling process was developed to achieve stable heavy gauge X80 mechanical properties. The importance of the slab reheating process and rolling schedule will be discussed in the paper. In addition, the per pass reductions logic used during recrystallized rough rolling, and special emphasis on the reduction of the final roughing pass prior to the intermediate holding resulting in a fine uniform prior austenite microstructure will be discussed. The optimized cooling process application after finish rolling guarantees the steady control of the final bainitic microstructure with optimum M/A phase for heavy gauge X80 plates. The plates produced by this process achieved good flatness and excellent mechanical properties. SQS has produced 10000 tons 27mm X80 for the Middle Asia C Line Project and 1000 tons 33mm X80 for the 3rd West-to-East Natural Gas Transmission Pipeline Project in 2013-2014. The products utilizing optimized rolling and cooling process showed extremely excellent low temperature toughness.

[Optimization of Formulation and Process of Paclitaxel PEGylated Liposomes by Box-Behnken Response Surface Methodology].

PubMed

Shi, Ya-jun; Zhang, Xiao-feil; Guo, Qiu-ting

2015-12-01

To develop a procedure for preparing paclitaxel encapsulated PEGylated liposomes. The membrane hydration followed extraction method was used to prepare PEGylated liposomes. The process and formulation variables were optimized by "Box-Behnken Design (BBD)" of response surface methodology (RSM) with the amount of Soya phosphotidylcholine (SPC) and PEG2000-DSPE as well as the rate of SPC to drug as independent variables and entrapment efficiency as dependent variables for optimization of formulation variables while temperature, pressure and cycle times as independent variables and particle size and polydispersion index as dependent variables for process variables. The optimized liposomal formulation was characterized for particle size, Zeta potential, morphology and in vitro drug release. For entrapment efficiency, particle size, polydispersion index, Zeta potential, and in vitro drug release of PEGylated liposomes was found to be 80.3%, (97.15 ± 14.9) nm, 0.117 ± 0.019, (-30.3 ± 3.7) mV, and 37.4% in 24 h, respectively. The liposomes were found to be small, unilamellar and spherical with smooth surface as seen in transmission electron microscopy. The Box-Behnken response surface methodology facilitates the formulation and optimization of paclitaxel PEGylated liposomes.

Optimal environmental management strategy and implementation for groundwater contamination prevention and restoration.

PubMed

Wang, Mingyu

2006-04-01

An innovative management strategy is proposed for optimized and integrated environmental management for regional or national groundwater contamination prevention and restoration allied with consideration of sustainable development. This management strategy accounts for availability of limited resources, human health and ecological risks from groundwater contamination, costs for groundwater protection measures, beneficial uses and values from groundwater protection, and sustainable development. Six different categories of costs are identified with regard to groundwater prevention and restoration. In addition, different environmental impacts from groundwater contamination including human health and ecological risks are individually taken into account. System optimization principles are implemented to accomplish decision-makings on the optimal resources allocations of the available resources or budgets to different existing contaminated sites and projected contamination sites for a maximal risk reduction. Established management constraints such as budget limitations under different categories of costs are satisfied at the optimal solution. A stepwise optimization process is proposed in which the first step is to select optimally a limited number of sites where remediation or prevention measures will be taken, from all the existing contaminated and projected contamination sites, based on a total regionally or nationally available budget in a certain time frame such as 10 years. Then, several optimization steps determined year-by-year optimal distributions of the available yearly budgets for those selected sites. A hypothetical case study is presented to demonstrate a practical implementation of the management strategy. Several issues pertaining to groundwater contamination exposure and risk assessments and remediation cost evaluations are briefly discussed for adequately understanding implementations of the management strategy.

Optimal decision making modeling for copper-matte Peirce-Smith converting process by means of data mining

NASA Astrophysics Data System (ADS)

Song, Yanpo; Peng, Xiaoqi; Tang, Ying; Hu, Zhikun

2013-07-01

To improve the operation level of copper converter, the approach to optimal decision making modeling for coppermatte converting process based on data mining is studied: in view of the characteristics of the process data, such as containing noise, small sample size and so on, a new robust improved ANN (artificial neural network) modeling method is proposed; taking into account the application purpose of decision making model, three new evaluation indexes named support, confidence and relative confidence are proposed; using real production data and the methods mentioned above, optimal decision making model for blowing time of S1 period (the 1st slag producing period) are developed. Simulation results show that this model can significantly improve the converting quality of S1 period, increase the optimal probability from about 70% to about 85%.

Manipulation and handling processes off-line programming and optimization with use of K-Roset

NASA Astrophysics Data System (ADS)

Gołda, G.; Kampa, A.

2017-08-01

Contemporary trends in development of efficient, flexible manufacturing systems require practical implementation of modern “Lean production” concepts for maximizing customer value through minimizing all wastes in manufacturing and logistics processes. Every FMS is built on the basis of automated and robotized production cells. Except flexible CNC machine tools and other equipments, the industrial robots are primary elements of the system. In the studies, authors look for wastes of time and cost in real tasks of robots, during manipulation processes. According to aspiration for optimization of handling and manipulation processes with use of the robots, the application of modern off-line programming methods and computer simulation, is the best solution and it is only way to minimize unnecessary movements and other instructions. The modelling process of robotized production cell and offline programming of Kawasaki robots in AS-Language will be described. The simulation of robotized workstation will be realized with use of virtual reality software K-Roset. Authors show the process of industrial robot’s programs improvement and optimization in terms of minimizing the number of useless manipulator movements and unnecessary instructions. This is realized in order to shorten the time of production cycles. This will also reduce costs of handling, manipulations and technological process.

A strategy to optimize the thermoelectric performance in a spark plasma sintering process

PubMed Central

Chiu, Wan-Ting; Chen, Cheng-Lung; Chen, Yang-Yuan

2016-01-01

Spark plasma sintering (SPS) is currently widely applied to existing alloys as a means of further enhancing the alloys’ figure of merit. However, the determination of the optimal sintering condition is challenging in the SPS process. This report demonstrates a systematic way to independently optimize the Seebeck coefficient S and the ratio of electrical to thermal conductivity (σ/κ) and thus achieve the maximum figure of merit zT = S2(σ/κ)T. Sb2−xInxTe3 (x = 0–0.2) were chosen as examples to validate the method. Although high sintering temperature and pressure are helpful in enhancing the compactness and electrical conductivity of pressed samples, the resultant deteriorated Seebeck coefficient and increasing thermal conductivity eventually offset the benefit. We found that the optimal sintering temperature coincides with temperatures at which the maximum Seebeck coefficient begins to degrade, whereas the optimal sintering pressure coincided with the pressure at which the σ/κ ratio reaches a maximum. Based on this principle, the optimized sintering conditions were determined, and the zT of Sb1.9In0.1Te3 is raised to 0.92 at 600 K, showing an approximately 84% enhancement. This work develops a facile strategy for selecting the optimal SPS sintering condition to further enhance the zT of bulk specimens. PMID:26975209

Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

PubMed Central

Young, Eric; Alper, Hal

2010-01-01

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research. PMID:20150964

Efficiency of quarantine and self-protection processes in epidemic spreading control on scale-free networks

NASA Astrophysics Data System (ADS)

Esquivel-Gómez, Jose de Jesus; Barajas-Ramírez, Juan Gonzalo

2018-01-01

One of the most effective mechanisms to contain the spread of an infectious disease through a population is the implementation of quarantine policies. However, its efficiency is affected by different aspects, for example, the structure of the underlining social network where highly connected individuals are more likely to become infected; therefore, the speed of the transmission of the decease is directly determined by the degree distribution of the network. Another aspect that influences the effectiveness of the quarantine is the self-protection processes of the individuals in the population, that is, they try to avoid contact with potentially infected individuals. In this paper, we investigate the efficiency of quarantine and self-protection processes in preventing the spreading of infectious diseases over complex networks with a power-law degree distribution [ P ( k ) ˜ k - ν ] for different ν values. We propose two alternative scale-free models that result in power-law degree distributions above and below the exponent ν = 3 associated with the conventional Barabási-Albert model. Our results show that the exponent ν determines the effectiveness of these policies in controlling the spreading process. More precisely, we show that for the ν exponent below three, the quarantine mechanism loses effectiveness. However, the efficiency is improved if the quarantine is jointly implemented with a self-protection process driving the number of infected individuals significantly lower.

Reduced order model based on principal component analysis for process simulation and optimization

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

Lang, Y.; Malacina, A.; Biegler, L.

2009-01-01

It is well-known that distributed parameter computational fluid dynamics (CFD) models provide more accurate results than conventional, lumped-parameter unit operation models used in process simulation. Consequently, the use of CFD models in process/equipment co-simulation offers the potential to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. Because solving CFD models is time-consuming compared to the overall process simulation, we consider the development of fast reduced order models (ROMs) based on CFD results to closely approximate the high-fidelity equipment models in the co-simulation. By considering process equipment items with complicated geometries and detailed thermodynamic property models,more » this study proposes a strategy to develop ROMs based on principal component analysis (PCA). Taking advantage of commercial process simulation and CFD software (for example, Aspen Plus and FLUENT), we are able to develop systematic CFD-based ROMs for equipment models in an efficient manner. In particular, we show that the validity of the ROM is more robust within well-sampled input domain and the CPU time is significantly reduced. Typically, it takes at most several CPU seconds to evaluate the ROM compared to several CPU hours or more to solve the CFD model. Two case studies, involving two power plant equipment examples, are described and demonstrate the benefits of using our proposed ROM methodology for process simulation and optimization.« less

Rational risk-based decision support for drinking water well managers by optimized monitoring designs

NASA Astrophysics Data System (ADS)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill

Stochastic optimal control of ultradiffusion processes with application to dynamic portfolio management

NASA Astrophysics Data System (ADS)

Marcozzi, Michael D.

2008-12-01

We consider theoretical and approximation aspects of the stochastic optimal control of ultradiffusion processes in the context of a prototype model for the selling price of a European call option. Within a continuous-time framework, the dynamic management of a portfolio of assets is effected through continuous or point control, activation costs, and phase delay. The performance index is derived from the unique weak variational solution to the ultraparabolic Hamilton-Jacobi equation; the value function is the optimal realization of the performance index relative to all feasible portfolios. An approximation procedure based upon a temporal box scheme/finite element method is analyzed; numerical examples are presented in order to demonstrate the viability of the approach.

A parylene coating process for hybrid circuits

NASA Technical Reports Server (NTRS)

1976-01-01

The parylene coating process developed during this program consists of (1) obtaining a hybrid cover with a hole in it, (2) sealing of the circuit with a hole in the cover, (3) parylene coating through the hole with the external leads protected from parylene by appropriate fixturing, and (4) sealing of the hole by soldering a pretinned kovar tab. Development of the above process required optimization of the parylene coater parameters to obtain a uniform consistent coating which could offer adequate protection to the circuits, fixture design for packages of various types, determination of the size of the deposition hole, and the amount of dimer charge per run, a process to hermetically seal the deposition holes and establishment of quality control techniques or acceptance criteria for the deposited film.

Approximation of optimal filter for Ornstein-Uhlenbeck process with quantised discrete-time observation

NASA Astrophysics Data System (ADS)

Bania, Piotr; Baranowski, Jerzy

2018-02-01

Quantisation of signals is a ubiquitous property of digital processing. In many cases, it introduces significant difficulties in state estimation and in consequence control. Popular approaches either do not address properly the problem of system disturbances or lead to biased estimates. Our intention was to find a method for state estimation for stochastic systems with quantised and discrete observation, that is free of the mentioned drawbacks. We have formulated a general form of the optimal filter derived by a solution of Fokker-Planck equation. We then propose the approximation method based on Galerkin projections. We illustrate the approach for the Ornstein-Uhlenbeck process, and derive analytic formulae for the approximated optimal filter, also extending the results for the variant with control. Operation is illustrated with numerical experiments and compared with classical discrete-continuous Kalman filter. Results of comparison are substantially in favour of our approach, with over 20 times lower mean squared error. The proposed filter is especially effective for signal amplitudes comparable to the quantisation thresholds. Additionally, it was observed that for high order of approximation, state estimate is very close to the true process value. The results open the possibilities of further analysis, especially for more complex processes.

Optimized shielding for space radiation protection

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Cucinotta, F. A.; Kim, M. H.; Schimmerling, W.

2001-01-01

Future deep space mission and International Space Station exposures will be dominated by the high-charge and -energy (HZE) ions of the Galactic Cosmic Rays (GCR). A few mammalian systems have been extensively tested over a broad range of ion types and energies. For example, C3H10T1/2 cells, V79 cells, and Harderian gland tumors have been described by various track-structure dependent response models. The attenuation of GCR induced biological effects depends strongly on the biological endpoint, response model used, and material composition. Optimization of space shielding is then driven by the nature of the response model and the transmission characteristics of the given material.

Contributions on Optimizing Approximations in the Study of Melting and Solidification Processes That Occur in Processing by Electro-Erosion

NASA Astrophysics Data System (ADS)

Potra, F. L.; Potra, T.; Soporan, V. F.

We propose two optimization methods of the processes which appear in EDM (Electrical Discharge Machining). First refers to the introduction of a new function approximating the thermal flux energy in EDM machine. Classical researches approximate this energy with the Gauss' function. In the case of unconventional technology the Gauss' bell became null only for r → +∞, where r is the radius of crater produced by EDM. We introduce a cubic spline regression which descends to zero at the crater's boundary. In the second optimization we propose modifications in technologies' work regarding the displacement of the tool electrode to the piece electrode such that the material melting to be realized in optimal time and the feeding speed with dielectric liquid regarding the solidification of the expulsed material. This we realize using the FAHP algorithm based on the theory of eigenvalues and eigenvectors, which lead to mean values of best approximation. [6

Integrated controls design optimization

DOEpatents

Lou, Xinsheng; Neuschaefer, Carl H.

2015-09-01

A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.

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.

Co-extrusion of food grains-banana pulp for nutritious snacks: optimization of process variables.

PubMed

Mridula, D; Sethi, Swati; Tushir, Surya; Bhadwal, Sheetal; Gupta, R K; Nanda, S K

2017-08-01

Present study was undertaken to optimize the process conditions for development of food grains (maize, defatted soy flour, sesame seed)-banana based nutritious expanded snacks using extrusion processing. Experiments were designed using Box-Behnken design with banana pulp (8-24 g), screw speed (300-350 rpm) and feed moisture (14-16% w.b.). Seven responses viz. expansion ratio (ER), bulk density (BD), water absorption index (WAI), protein, minerals, iron and sensory acceptability were considered for optimizing independent parameters. ER, BD, WAI, protein content, total minerals, iron content, and overall acceptability ranged 2.69-3.36, 153.43-238.83 kg/m 3 , 4.56-4.88 g/g, 15.19-15.52%, 2.06-2.27%, 4.39-4.67 mg/100 g (w.b.) and 6.76-7.36, respectively. ER was significantly affected by all three process variables while BD was influenced by banana pulp and screw speed only. Studied process variables did not affected colour quality except 'a' value with banana pulp and screw speed. Banana pulp had positive correlation with water solubility index, total minerals and iron content and negative with WAI, protein and overall acceptability. Based upon multiple response analysis, optimized conditions were 8 g banana pulp, 350 rpm screw speed and 14% feed moisture indicating the protein, calorie, iron content and overall sensory acceptability in sample as 15.46%, 401 kcal/100 g, 4.48 mg/100 g and 7.6 respectively.

Flat-plate photovoltaic array design optimization

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.

1980-01-01

An analysis is presented which integrates the results of specific studies in the areas of photovoltaic structural design optimization, optimization of array series/parallel circuit design, thermal design optimization, and optimization of environmental protection features. The analysis is based on minimizing the total photovoltaic system life-cycle energy cost including repair and replacement of failed cells and modules. This approach is shown to be a useful technique for array optimization, particularly when time-dependent parameters such as array degradation and maintenance are involved.

A Big Data-driven Model for the Optimization of Healthcare Processes.

PubMed

Koufi, Vassiliki; Malamateniou, Flora; Vassilacopoulos, George

2015-01-01

Healthcare organizations increasingly navigate a highly volatile, complex environment in which technological advancements and new healthcare delivery business models are the only constants. In their effort to out-perform in this environment, healthcare organizations need to be agile enough in order to become responsive to these increasingly changing conditions. To act with agility, healthcare organizations need to discover new ways to optimize their operations. To this end, they focus on healthcare processes that guide healthcare delivery and on the technologies that support them. Business process management (BPM) and Service-Oriented Architecture (SOA) can provide a flexible, dynamic, cloud-ready infrastructure where business process analytics can be utilized to extract useful insights from mountains of raw data, and make them work in ways beyond the abilities of human brains, or IT systems from just a year ago. This paper presents a framework which provides healthcare professionals gain better insight within and across your business processes. In particular, it performs real-time analysis on process-related data in order reveal areas of potential process improvement.

To protect or abandon: a participatory process on landslide risk mitigation

NASA Astrophysics Data System (ADS)

Scolobig, A.; Bayer, J.; Cascini, L.; Ferlisi, S.

2012-04-01

With escalating costs of landslide risk mitigation and relief, a challenge for local authorities is to develop landslide risk mitigation measures that are viewed as efficient, feasible and fair by the many stakeholders involved. Innovative measures and the participation of stakeholders in the decision making process are essential elements in developing effective strategies to deal with the ever-changing spatial and temporal patterns of landslide risk. A stakeholder-led policy process, however, can face many social and economic challenges. One of the most difficult is deciding between costly protection measures or relocating homes. Particularly in areas with high population density, protection works are often not built because of economic/environmental constraints or private interests of the local residents. At the same time it not always possible to relocate households even if the costs are deemed less than protecting them. These issues turned out to be crucial in a recent participatory process for selecting risk mitigation measures in the town of Nocera Inferiore, Southern Italy, which experienced a landslide in 2005 causing three fatalities. The paper reports on this process which was structured in a series of meetings with a group of selected residents and several parallel activities open to the public. The preparatory work included semi-structured interviews carried out with key local stakeholders and a public survey eliciting residents' views on landslide risk mitigation. After describing the background of the landslide risk management problem in Nocera Inferiore, the paper focuses on three packages of risk mitigation measures (each of them not exceeding a total cost of 7 million Euro, namely the available funds) and the key trade-offs that emerged during the meetings with the residents. The participants reached a unanimous consensus on fundamental priorities, i.e. the improvement of the warning system, the implementation of an integrated system of monitoring

Thermal protection of β-carotene in re-assembled casein micelles during different processing technologies applied in food industry.

PubMed

Sáiz-Abajo, María-José; González-Ferrero, Carolina; Moreno-Ruiz, Ana; Romo-Hualde, Ana; González-Navarro, Carlos J

2013-06-01

β-Carotene is a carotenoid usually applied in the food industry as a precursor of vitamin A or as a colourant. β-Carotene is a labile compound easily degraded by light, heat and oxygen. Casein micelles were used as nanostructures to encapsulate, stabilise and protect β-carotene from degradation during processing in the food industry. Self-assembly method was applied to re-assemble nanomicelles containing β-carotene. The protective effect of the nanostructures against degradation during the most common industrial treatments (sterilisation, pasteurisation, high hydrostatic pressure and baking) was proven. Casein micelles protected β-carotene from degradation during heat stabilisation, high pressure processing and the processes most commonly used in the food industry including baking. This opens new possibilities for introducing thermolabile ingredients in bakery products. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Optimization of extraction process for tannins from Geranium orientali-tibeticum by supercritical CO2 method].

PubMed

Xie, Song; Tong, Zhi-Ping; Tan, Rui; Liu, Xiao-Zhen

2014-08-01

In order to optimize extraction process conditions of tannins from Geranium orientali-tibeticum by supercritical CO2, the content of tannins was determined by phosphomolybdium tungsten acid-casein reaction, with extraction pressure, extraction temper- ature and extraction time as factors, the content of tannins from extract of G. orientali-tibeticum as index, technology conditions were optimized by orthogonal test. Optimum technology conditions were as follows: extraction pressure was 25 MPa, extraction temperature was 50 °C, extracted 1.5 h. The content of tannins in extract was 12.91 mg x g(-1), extract rate was 3.67%. The method established could be used for assay the contents of tannin in G. orientali-tibeticum. The circulated extraction was an effective extraction process that was stable and feasible, and that provides a way of the extraction process conditions of tannin from G. orientali-tibeticum.

77 FR 10657 - Protecting the Public and Our Employees in Our Hearing Process

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-23

... SOCIAL SECURITY ADMINISTRATION 20 CFR Parts 404 and 416 [Docket No. SSA-2011-0008] RIN 0960-AH29 Protecting the Public and Our Employees in Our Hearing Process AGENCY: Social Security Administration. ACTION... INFORMATION CONTACT: Glen Colvin, Social Security Administration, 5107 Leesburg Pike, Falls Church, VA 22041...

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.

Management of unmanned moving sensors through human decision layers: a bi-level optimization process with calls to costly sub-processes

NASA Astrophysics Data System (ADS)

Dambreville, Frédéric

2013-10-01

While there is a variety of approaches and algorithms for optimizing the mission of an unmanned moving sensor, there are much less works which deal with the implementation of several sensors within a human organization. In this case, the management of the sensors is done through at least one human decision layer, and the sensors management as a whole arises as a bi-level optimization process. In this work, the following hypotheses are considered as realistic: Sensor handlers of first level plans their sensors by means of elaborated algorithmic tools based on accurate modelling of the environment; Higher level plans the handled sensors according to a global observation mission and on the basis of an approximated model of the environment and of the first level sub-processes. This problem is formalized very generally as the maximization of an unknown function, defined a priori by sampling a known random function (law of model error). In such case, each actual evaluation of the function increases the knowledge about the function, and subsequently the efficiency of the maximization. The issue is to optimize the sequence of value to be evaluated, in regards to the evaluation costs. There is here a fundamental link with the domain of experiment design. Jones, Schonlau and Welch proposed a general method, the Efficient Global Optimization (EGO), for solving this problem in the case of additive functional Gaussian law. In our work, a generalization of the EGO is proposed, based on a rare event simulation approach. It is applied to the aforementioned bi-level sensor planning.

Optimization of prehydrolysis time and substrate feeding to improve ethanol production by simultaneous saccharification and fermentation of furfural process residue.

PubMed

He, Jianlong; Zhang, Wenbo; Liu, Xiaoyan; Xu, Ning; Xiong, Peng

2016-11-01

Ethanol is a very important industrial chemical. In order to improve ethanol productivity using Saccharomyces cerevisiae in fermentation from furfural process residue, we developed a process of simultaneous saccharification and fermentation (SSF) of furfural process residue, optimizing prehydrolysis cellulase loading concentration, prehydrolysis time, and substrate feeding strategy. The ethanol concentration obtained from the optimized process was 19.3 g/L, corresponding 76.5% ethanol yield, achieved by running SSF for 48 h from 10% furfural process residue with prehydrolysis at 50°C for 4 h and cellulase loading of 15 FPU/g furfural process residue. For higher ethanol concentrations, fed-batch fermentation was performed. The optimized fed-batch process increased the ethanol concentration to 37.6 g/L, 74.5% yield, obtained from 10% furfural process residue with two additions of 5% substrate at 12 and 24 h. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.