Uncertainty Quantification for Polynomial Systems via Bernstein Expansions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2012-01-01

This paper presents a unifying framework to uncertainty quantification for systems having polynomial response metrics that depend on both aleatory and epistemic uncertainties. The approach proposed, which is based on the Bernstein expansions of polynomials, enables bounding the range of moments and failure probabilities of response metrics as well as finding supersets of the extreme epistemic realizations where the limits of such ranges occur. These bounds and supersets, whose analytical structure renders them free of approximation error, can be made arbitrarily tight with additional computational effort. Furthermore, this framework enables determining the importance of particular uncertain parameters according to the extent to which they affect the first two moments of response metrics and failure probabilities. This analysis enables determining the parameters that should be considered uncertain as well as those that can be assumed to be constants without incurring significant error. The analytical nature of the approach eliminates the numerical error that characterizes the sampling-based techniques commonly used to propagate aleatory uncertainties as well as the possibility of under predicting the range of the statistic of interest that may result from searching for the best- and worstcase epistemic values via nonlinear optimization or sampling.

Optimally robust redundancy relations for failure detection in uncertain systems

NASA Technical Reports Server (NTRS)

Lou, X.-C.; Willsky, A. S.; Verghese, G. C.

1986-01-01

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper the problem of determining redundancy relations that are optimally robust is addressed in a sense that includes several major issues of importance in practical failure detection and that provides a significant amount of intuition concerning the geometry of robust failure detection. A procedure is given involving the construction of a single matrix and its singular value decomposition for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

Analysis and Reduction of Complex Networks Under Uncertainty.

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

Ghanem, Roger G

2014-07-31

This effort was a collaboration with Youssef Marzouk of MIT, Omar Knio of Duke University (at the time at Johns Hopkins University) and Habib Najm of Sandia National Laboratories. The objective of this effort was to develop the mathematical and algorithmic capacity to analyze complex networks under uncertainty. Of interest were chemical reaction networks and smart grid networks. The statements of work for USC focused on the development of stochastic reduced models for uncertain networks. The USC team was led by Professor Roger Ghanem and consisted of one graduate student and a postdoc. The contributions completed by the USC teammore » consisted of 1) methodology and algorithms to address the eigenvalue problem, a problem of significance in the stability of networks under stochastic perturbations, 2) methodology and algorithms to characterize probability measures on graph structures with random flows. This is an important problem in characterizing random demand (encountered in smart grid) and random degradation (encountered in infrastructure systems), as well as modeling errors in Markov Chains (with ubiquitous relevance !). 3) methodology and algorithms for treating inequalities in uncertain systems. This is an important problem in the context of models for material failure and network flows under uncertainty where conditions of failure or flow are described in the form of inequalities between the state variables.« less

When, not if: the inescapability of an uncertain climate future.

PubMed

Ballard, Timothy; Lewandowsky, Stephan

2015-11-28

Climate change projections necessarily involve uncertainty. Analysis of the physics and mathematics of the climate system reveals that greater uncertainty about future temperature increases is nearly always associated with greater expected damages from climate change. In contrast to those normative constraints, uncertainty is frequently cited in public discourse as a reason to delay mitigative action. This failure to understand the actual implications of uncertainty may incur notable future costs. It is therefore important to communicate uncertainty in a way that improves people's understanding of climate change risks. We examined whether responses to projections were influenced by whether the projection emphasized uncertainty in the outcome or in its time of arrival. We presented participants with statements and graphs indicating projected increases in temperature, sea levels, ocean acidification and a decrease in arctic sea ice. In the uncertain-outcome condition, statements reported the upper and lower confidence bounds of the projected outcome at a fixed time point. In the uncertain time-of-arrival condition, statements reported the upper and lower confidence bounds of the projected time of arrival for a fixed outcome. Results suggested that people perceived the threat as more serious and were more likely to encourage mitigative action in the time-uncertain condition than in the outcome-uncertain condition. This finding has implications for effectively communicating the climate change risks to policy-makers and the general public. © 2015 The Author(s).

[The acute phase, a time which determines the outcome of a patient with a head trauma].

PubMed

Jeauneaux, Olivier; Bony, Maylis; Giroud, Olivier; Chabert, Flavien; Pagnier, Daniel; Mansuy, Charlène; Quélin, Pauline; Lemperrière, Héloïse; Grodecœur, Caroline; Armonia, Cécile

2017-03-01

As soon as their prehospital care begins, patients with a serious head injury are given intensive care to offset the systemic failures observed and minimise secondary brain damage. In intensive care, monitoring is continuous and neuroprotection optimised. While the prognosis of the patient remains uncertain, their family are included and involved in their global care. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.

The hydraulic capacity of deteriorating sewer systems.

PubMed

Pollert, J; Ugarelli, R; Saegrov, S; Schilling, W; Di Federico, V

2005-01-01

Sewer and wastewater systems suffer from insufficient capacity, construction flaws and pipe deterioration. Consequences are structural failures, local floods, surface erosion and pollution of receiving waters bodies. European cities spend in the order of five billion Euro per year for wastewater network rehabilitation. This amount is estimated to increase due to network ageing. The project CARE-S (Computer Aided RE-habilitation of Sewer Networks) deals with sewer and storm water networks. The final project goal is to develop integrated software, which provides the most cost-efficient system of maintenance, repair and rehabilitation of sewer networks. Decisions on investments in rehabilitation often have to be made with uncertain information about the structural condition and the hydraulic performance of a sewer system. Because of this, decision-making involves considerable risks. This paper presents the results of research focused on the study of hydraulic effects caused by failures due to temporal decline of sewer systems. Hydraulic simulations are usually carried out by running commercial models that apply, as input, default values of parameters that strongly influence results. Using CCTV inspections information as dataset to catalogue principal types of failures affecting pipes, a 3D model was used to evaluate their hydraulic consequences. The translation of failures effects in parameters values producing the same hydraulic conditions caused by failures was carried out through the comparison of laboratory experiences and 3D simulations results. Those parameters could be the input of 1D commercial models instead of the default values commonly inserted.

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

Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink,more » improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.« less

POF-Darts: Geometric adaptive sampling for probability of failure

DOE PAGES

Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.; ...

2016-06-18

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink,more » improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.« less

Experimental Robot Position Sensor Fault Tolerance Using Accelerometers and Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. The proposed method uses joint torque sensors found in most existing advanced robot designs along with easily locatable, lightweight accelerometers to provide a joint position sensor fault recovery mode. This mode uses the torque sensors along with a virtual passive control law for stability and accelerometers for joint position information. Two methods for conversion from Cartesian acceleration to joint position based on robot kinematics, not integration, are presented. The fault tolerant control method was tested on several joints of a laboratory robot. The controllers performed well with noisy, biased data and a model with uncertain parameters.

Common Cause Failure Modeling in Space Launch Vehicles

NASA Technical Reports Server (NTRS)

Hark, Frank; Ring, Rob; Novack, Steven D.; Britton, Paul

2015-01-01

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFs are a set of dependent type of failures that can be caused for example by system environments, manufacturing, transportation, storage, maintenance, and assembly. Since there are many factors that contribute to CCFs, they can be reduced, but are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and dependent CCF. Because common cause failure data is limited in the aerospace industry, the Probabilistic Risk Assessment (PRA) Team at Bastion Technology Inc. is estimating CCF risk using generic data collected by the Nuclear Regulatory Commission (NRC). Consequently, common cause risk estimates based on this database, when applied to other industry applications, are highly uncertain. Therefore, it is important to account for a range of values for independent and CCF risk and to communicate the uncertainty to decision makers. There is an existing methodology for reducing CCF risk during design, which includes a checklist of 40+ factors grouped into eight categories. Using this checklist, an approach to produce a beta factor estimate is being investigated that quantitatively relates these factors. In this example, the checklist will be tailored to space launch vehicles, a quantitative approach will be described, and an example of the method will be presented.

Data-based fault-tolerant control of high-speed trains with traction/braking notch nonlinearities and actuator failures.

PubMed

Song, Qi; Song, Yong-Duan

2011-12-01

This paper investigates the position and velocity tracking control problem of high-speed trains with multiple vehicles connected through couplers. A dynamic model reflecting nonlinear and elastic impacts between adjacent vehicles as well as traction/braking nonlinearities and actuation faults is derived. Neuroadaptive fault-tolerant control algorithms are developed to account for various factors such as input nonlinearities, actuator failures, and uncertain impacts of in-train forces in the system simultaneously. The resultant control scheme is essentially independent of system model and is primarily data-driven because with the appropriate input-output data, the proposed control algorithms are capable of automatically generating the intermediate control parameters, neuro-weights, and the compensation signals, literally producing the traction/braking force based upon input and response data only--the whole process does not require precise information on system model or system parameter, nor human intervention. The effectiveness of the proposed approach is also confirmed through numerical simulations.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

Robust reliable sampled-data control for switched systems with application to flight control

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Joby, Maya; Shi, P.; Mathiyalagan, K.

2016-11-01

This paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov-Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.

On-board fault management for autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Doyle, Susan C.; Martin, Eric; Sellers, Suzanne

1991-01-01

The dynamic nature of the Cargo Transfer Vehicle's (CTV) mission and the high level of autonomy required mandate a complete fault management system capable of operating under uncertain conditions. Such a fault management system must take into account the current mission phase and the environment (including the target vehicle), as well as the CTV's state of health. This level of capability is beyond the scope of current on-board fault management systems. This presentation will discuss work in progress at TRW to apply artificial intelligence to the problem of on-board fault management. The goal of this work is to develop fault management systems. This presentation will discuss work in progress at TRW to apply artificial intelligence to the problem of on-board fault management. The goal of this work is to develop fault management systems that can meet the needs of spacecraft that have long-range autonomy requirements. We have implemented a model-based approach to fault detection and isolation that does not require explicit characterization of failures prior to launch. It is thus able to detect failures that were not considered in the failure and effects analysis. We have applied this technique to several different subsystems and tested our approach against both simulations and an electrical power system hardware testbed. We present findings from simulation and hardware tests which demonstrate the ability of our model-based system to detect and isolate failures, and describe our work in porting the Ada version of this system to a flight-qualified processor. We also discuss current research aimed at expanding our system to monitor the entire spacecraft.

SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Knowledge Advancement.

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

Gauntt, Randall O.; Mattie, Patrick D.; Bixler, Nathan E.

2014-02-01

This paper describes the knowledge advancements from the uncertainty analysis for the State-of- the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout accident scenario at the Peach Bottom Atomic Power Station. This work assessed key MELCOR and MELCOR Accident Consequence Code System, Version 2 (MACCS2) modeling uncertainties in an integrated fashion to quantify the relative importance of each uncertain input on potential accident progression, radiological releases, and off-site consequences. This quantitative uncertainty analysis provides measures of the effects on consequences, of each of the selected uncertain parameters both individually and in interaction with other parameters. The results measure the modelmore » response (e.g., variance in the output) to uncertainty in the selected input. Investigation into the important uncertain parameters in turn yields insights into important phenomena for accident progression and off-site consequences. This uncertainty analysis confirmed the known importance of some parameters, such as failure rate of the Safety Relief Valve in accident progression modeling and the dry deposition velocity in off-site consequence modeling. The analysis also revealed some new insights, such as dependent effect of cesium chemical form for different accident progressions. (auth)« less

Using Markov Models of Fault Growth Physics and Environmental Stresses to Optimize Control Actions

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by a uniformly distributed dice throwing process, and a discrete random walk is used to represent uncertain modeling of future exogenous loading demands to be placed on the system. A finite horizon dynamic programming algorithm is used to solve for an optimal control policy over a finite time window for the case that stochastic models representing physics of failure and future environmental stresses are known, and the states of both stochastic processes are observable by implemented control routines. The fundamental limitations of optimization performed in the presence of uncertain modeling information are examined by comparing the outcomes obtained from simulations of an optimizing control policy with the outcomes that would be achievable if all modeling uncertainties were removed from the system.

Reliability-Based Control Design for Uncertain Systems

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Causal uncertainty, claimed and behavioural self-handicapping.

PubMed

Thompson, Ted; Hepburn, Jonathan

2003-06-01

Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.

A fuzzy case based reasoning tool for model based approach to rocket engine health monitoring

NASA Technical Reports Server (NTRS)

Krovvidy, Srinivas; Nolan, Adam; Hu, Yong-Lin; Wee, William G.

1992-01-01

In this system we develop a fuzzy case based reasoner that can build a case representation for several past anomalies detected, and we develop case retrieval methods that can be used to index a relevant case when a new problem (case) is presented using fuzzy sets. The choice of fuzzy sets is justified by the uncertain data. The new problem can be solved using knowledge of the model along with the old cases. This system can then be used to generalize the knowledge from previous cases and use this generalization to refine the existing model definition. This in turn can help to detect failures using the model based algorithms.

Robust fault tolerant control based on sliding mode method for uncertain linear systems with quantization.

PubMed

Hao, Li-Ying; Yang, Guang-Hong

2013-09-01

This paper is concerned with the problem of robust fault-tolerant compensation control problem for uncertain linear systems subject to both state and input signal quantization. By incorporating novel matrix full-rank factorization technique with sliding surface design successfully, the total failure of certain actuators can be coped with, under a special actuator redundancy assumption. In order to compensate for quantization errors, an adjustment range of quantization sensitivity for a dynamic uniform quantizer is given through the flexible choices of design parameters. Comparing with the existing results, the derived inequality condition leads to the fault tolerance ability stronger and much wider scope of applicability. With a static adjustment policy of quantization sensitivity, an adaptive sliding mode controller is then designed to maintain the sliding mode, where the gain of the nonlinear unit vector term is updated automatically to compensate for the effects of actuator faults, quantization errors, exogenous disturbances and parameter uncertainties without the need for a fault detection and isolation (FDI) mechanism. Finally, the effectiveness of the proposed design method is illustrated via a model of a rocket fairing structural-acoustic. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

How Systems Engineering and Risk Management Defend Against Murphy's Law and Human Error

NASA Technical Reports Server (NTRS)

Bay, Michael; Connley, Warren

2004-01-01

Systems Engineering and Risk Management processes can work synergistically to defend against the causes of many mission ending failures. Defending against mission ending failures is facilitated by fostering a team that has a healthy respect for Murphy's Law and a team with a of curiosity for how things work, how they can fail, and what they need to know. This curiosity is channeled into making the unknowns known or what is uncertain more certain. Efforts to assure mission success require the expenditure of energy in the following areas: 1. Understanding what defines Mission Success as guided by the customer's needs, objectives and constraints. 2. Understanding how the system is supposed to work and how the system is to be produced, fueled by the curiosity of how the system should work and how it should be produced. 3. Understanding how the system can fail and how the system might not be produced on time and within cost, fueled by the curiosity of how the system might fail and how production might be difficult. 4. Understanding what we need to know and what we need learn for proper completion of the above three items, fueled by the curiosity of what we might not know in order to make the best decisions.

Towards Real-time, On-board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Rozier, Kristin Y.; Reinbacher, Thomas; Mengshoel, Ole J.; Mbaya, Timmy; Ippolito, Corey

2013-01-01

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) capability to continuously monitor sensors, software, and hardware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and/or software signals; (2) signal analysis, preprocessing, and advanced on the- fly temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software due to instrumentation. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual data from the NASA Swift UAS, an experimental all-electric aircraft.

Adaptive Controller Effects on Pilot Behavior

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

2014-01-01

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

Modal-space reference-model-tracking fuzzy control of earthquake excited structures

NASA Astrophysics Data System (ADS)

Park, Kwan-Soon; Ok, Seung-Yong

2015-01-01

This paper describes an adaptive modal-space reference-model-tracking fuzzy control technique for the vibration control of earthquake-excited structures. In the proposed approach, the fuzzy logic is introduced to update optimal control force so that the controlled structural response can track the desired response of a reference model. For easy and practical implementation, the reference model is constructed by assigning the target damping ratios to the first few dominant modes in modal space. The numerical simulation results demonstrate that the proposed approach successfully achieves not only the adaptive fault-tolerant control system against partial actuator failures but also the robust performance against the variations of the uncertain system properties by redistributing the feedback control forces to the available actuators.

ORCHID - a computer simulation of the reliability of an NDE inspection system

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

Moles, M.D.C.

1987-03-01

CANDU pressurized heavy water reactors contain several hundred horizontally-mounted zirconium alloy pressure tubes. Following a pressure tube failure, a pressure tube inspection system called CIGARette was rapidly designed, manufactured and put in operation. Defects called hydride blisters were found to be the cause of the failure, and were detected using a combination of eddy current and ultrasonic scans. A number of improvements were made to CIGARette during the inspection period. The ORCHID computer program models the operation of the delivery system, eddy current and ultrasonic systems by imitating the on-reactor decision-making procedure. ORCHID predicts that during the early stage ofmore » development, less than one blistered tube in three would be detected, while less than one in two would be detected in the middle development stage. However, ORCHID predicts that during the late development stage, probability of detection will be over 90%, primarily due to the inclusion of axial ultrasonic scans (a procedural modification). Rotational and axial slip could severely reduce probability of detection. Comparison of CIGARette's inspection data with ORCHID's predictions indicate that the latter are compatible with the actual inspection results, through the numbers are small and data uncertain. It should be emphasized that the CIGARette system has been essentially replaced with the much more reliable CIGAR system.« less

Timing of Pregnancy After Kidney Transplantation and Risk of Allograft Failure.

PubMed

Rose, C; Gill, J; Zalunardo, N; Johnston, O; Mehrotra, A; Gill, J S

2016-08-01

The optimal timing of pregnancy after kidney transplantation remains uncertain. We determined the risk of allograft failure among women who became pregnant within the first 3 posttransplant years. Among 21 814 women aged 15-45 years who received a first kidney-only transplant between 1990 and 2010 captured in the United States Renal Data System, n = 729 pregnancies were identified using Medicare claims. The probability of allograft failure from any cause including death (ACGL) at 1, 3, and 5 years after pregnancy was 9.6%, 25.9%, and 36.6%. In multivariate analyses, pregnancy in the first posttransplant year was associated with an increased risk of ACGL (hazard ratio [HR]: 1.18; 95% confidence interval [CI] 1.00, 1.40) and death censored graft loss (DCGL) (HR:1.25; 95% CI 1.04, 1.50), while pregnancy in the second posttransplant year was associated with an increased risk of DCGL (HR: 1.26; 95% CI 1.06, 1.50). Pregnancy in the third posttransplant year was not associated with an increased risk of ACGL or DCGL. These findings demonstrate a higher incidence of allograft failure after pregnancy than previously reported and that the increased risk of allograft failure extends to pregnancies in the second posttransplant year. © Copyright 2016 The American Society of Transplantation and the American Society of Transplant Surgeons.

Lognormal Uncertainty Estimation for Failure Rates

NASA Technical Reports Server (NTRS)

Britton, Paul T.; Al Hassan, Mohammad; Ring, Robert W.

2017-01-01

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain. Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This presentation will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

PubMed

Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

2011-04-01

This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

Adaptive route choice modeling in uncertain traffic networks with real-time information.

DOT National Transportation Integrated Search

2013-03-01

The objective of the research is to study travelers' route choice behavior in uncertain traffic networks : with real-time information. The research is motivated by two observations of the traffic system: 1) : the system is inherently uncertain with r...

A fuzzy set approach for reliability calculation of valve controlling electric actuators

NASA Astrophysics Data System (ADS)

Karmachev, D. P.; Yefremov, A. A.; Luneva, E. E.

2017-02-01

The oil and gas equipment and electric actuators in particular frequently perform in various operational modes and under dynamic environmental conditions. These factors affect equipment reliability measures in a vague, uncertain way. To eliminate the ambiguity, reliability model parameters could be defined as fuzzy numbers. We suggest a technique that allows constructing fundamental fuzzy-valued performance reliability measures based on an analysis of electric actuators failure data in accordance with the amount of work, completed before the failure, instead of failure time. Also, this paper provides a computation example of fuzzy-valued reliability and hazard rate functions, assuming Kumaraswamy complementary Weibull geometric distribution as a lifetime (reliability) model for electric actuators.

Public Response to a Near-Miss Nuclear Accident Scenario Varying in Causal Attributions and Outcome Uncertainty.

PubMed

Cui, Jinshu; Rosoff, Heather; John, Richard S

2018-05-01

Many studies have investigated public reactions to nuclear accidents. However, few studies focused on more common events when a serious accident could have happened but did not. This study evaluated public response (emotional, cognitive, and behavioral) over three phases of a near-miss nuclear accident. Simulating a loss-of-coolant accident (LOCA) scenario, we manipulated (1) attribution for the initial cause of the incident (software failure vs. cyber terrorist attack vs. earthquake), (2) attribution for halting the incident (fail-safe system design vs. an intervention by an individual expert vs. a chance coincidence), and (3) level of uncertainty (certain vs. uncertain) about risk of a future radiation leak after the LOCA is halted. A total of 773 respondents were sampled using a 3 × 3 × 2 between-subjects design. Results from both MANCOVA and structural equation modeling (SEM) indicate that respondents experienced more negative affect, perceived more risk, and expressed more avoidance behavioral intention when the near-miss event was initiated by an external attributed source (e.g., earthquake) compared to an internally attributed source (e.g., software failure). Similarly, respondents also indicated greater negative affect, perceived risk, and avoidance behavioral intentions when the future impact of the near-miss incident on people and the environment remained uncertain. Results from SEM analyses also suggested that negative affect predicted risk perception, and both predicted avoidance behavior. Affect, risk perception, and avoidance behavior demonstrated high stability (i.e., reliability) from one phase to the next. © 2017 Society for Risk Analysis.

Effect of Joule heating and current crowding on electromigration in mobile technology

NASA Astrophysics Data System (ADS)

Tu, K. N.; Liu, Yingxia; Li, Menglu

2017-03-01

In the present era of big data and internet of things, the use of microelectronic products in all aspects of our life is manifested by the ubiquitous presence of mobile devices as i-phones and wearable i-products. These devices are facing the need for higher power and greater functionality applications such as in i-health, yet they are limited by physical size. At the moment, software (Apps) is much ahead of hardware in mobile technology. To advance hardware, the end of Moore's law in two-dimensional integrated circuits can be extended by three-dimensional integrated circuits (3D ICs). The concept of 3D ICs has been with us for more than ten years. The challenge in 3D IC technology is dense packing by using both vertical and horizontal interconnections. Mass production of 3D IC devices is behind schedule due to cost because of low yield and uncertain reliability. Joule heating is serious in a dense structure because of heat generation and dissipation. A change of reliability paradigm has advanced from failure at a specific circuit component to failure at a system level weak-link. Currently, the electronic industry is introducing 3D IC devices in mainframe computers, where cost is not an issue, for the purpose of collecting field data of failure, especially the effect of Joule heating and current crowding on electromigration. This review will concentrate on the positive feedback between Joule heating and electromigration, resulting in an accelerated system level weak-link failure. A new driving force of electromigration, the electric potential gradient force due to current crowding, will be reviewed critically. The induced failure tends to occur in the low current density region.

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

Grabaskas, David; Brunett, Acacia J.; Passerini, Stefano

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examinedmore » utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.« less

Bayes Analysis and Reliability Implications of Stress-Rupture Testing a Kevlar/Epoxy COPV Using Temperature and Pressure Acceleration

NASA Technical Reports Server (NTRS)

Phoenix, S. Leigh; Kezirian, Michael T.; Murthy, Pappu L. N.

2009-01-01

Composite Overwrapped Pressure Vessels (COPVs) that have survived a long service time under pressure generally must be recertified before service is extended. Flight certification is dependent on the reliability analysis to quantify the risk of stress rupture failure in existing flight vessels. Full certification of this reliability model would require a statistically significant number of lifetime tests to be performed and is impractical given the cost and limited flight hardware for certification testing purposes. One approach to confirm the reliability model is to perform a stress rupture test on a flight COPV. Currently, testing of such a Kevlar49 (Dupont)/epoxy COPV is nearing completion. The present paper focuses on a Bayesian statistical approach to analyze the possible failure time results of this test and to assess the implications in choosing between possible model parameter values that in the past have had significant uncertainty. The key uncertain parameters in this case are the actual fiber stress ratio at operating pressure, and the Weibull shape parameter for lifetime; the former has been uncertain due to ambiguities in interpreting the original and a duplicate burst test. The latter has been uncertain due to major differences between COPVs in the database and the actual COPVs in service. Any information obtained that clarifies and eliminates uncertainty in these parameters will have a major effect on the predicted reliability of the service COPVs going forward. The key result is that the longer the vessel survives, the more likely the more optimistic stress ratio model is correct. At the time of writing, the resulting effect on predicted future reliability is dramatic, increasing it by about one "nine," that is, reducing the predicted probability of failure by an order of magnitude. However, testing one vessel does not change the uncertainty on the Weibull shape parameter for lifetime since testing several vessels would be necessary.

Carvedilol case history: the discovery and development of the first β-blocker for the treatment of congestive heart failure.

PubMed

Ruffolo, Robert R; Feuerstein, Giora Z

2006-06-01

Carvedilol is a multiple action drug that blocks β1-, β2- and α1- adrenoceptors, and has potent antioxidant properties. Carvedilol is the first drug of its kind to be approved for the treatment of congestive heart failure, and is now the standard of care for this devastating disease. The discovery and development of carvedilol encountered an adverse regulatory climate, skepticism by the cardiology community and hesitance by the company, and in the early 1990s, the fate of the drug was uncertain. Nonetheless, in the largest heart failure study conducted up until that point, carvedilol produced marked reductions in morbidity and mortality, and has given new hope to patients afflicted with congestive heart failure. The story behind carvedilol contains important observations and lessons for scientists, regulators and physicians.

Thought disorder in schizophrenia: impairment in contextual processing via integrative failures in cognition.

PubMed

Patniyot, Nicholas S

2011-10-01

Formal thought disorder is a critical dysfunction in schizophrenia whose cause remains uncertain, but whose explanation may greatly further our understanding of the disease. Thought disorder in patients with schizophrenia has been hypothesized to involve a disturbance in the internal representation of context. Positive symptoms of schizophrenia attributable to thought disorder display a lack of organization that may be accounted for by an absence of normal contextual processing occurring within the operations of the executive system. But the precise nature and pervasiveness of the deficient cognitive operation remain undistinguished. It is proposed here that the assimilatory functions of the brain appear to lack the ability to perform a particular type of integrative operation when presented with heterogeneous information. This deficit involves committing cognitive misattributions through a confusion of mental terms via a process in thought analogous to a linguistic failure to correctly interpret deictic referents. Both proposed deficits in mental deixis and analogous "metarepresentational" deficits in schizophrenia potentially involve a failure to draw information for a conclusion from a separate framework of relations in integrative fashion. These deficits appear to involve a failure to take an interpreted piece of information as an output from a particular mental task and incorporate it into a new operational scheme, and a central attribute to the deficit is that there is a loss of an effective or adequate integration of separate strata of information. Potential neurobiological correlates to such a system based on current knowledge about schizophrenia neurocircuitry, as well as implications for testing, are also discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

A linear quadratic regulator approach to the stabilization of uncertain linear systems

NASA Technical Reports Server (NTRS)

Shieh, L. S.; Sunkel, J. W.; Wang, Y. J.

1990-01-01

This paper presents a linear quadratic regulator approach to the stabilization of uncertain linear systems. The uncertain systems under consideration are described by state equations with the presence of time-varying unknown-but-bounded uncertainty matrices. The method is based on linear quadratic regulator (LQR) theory and Liapunov stability theory. The robust stabilizing control law for a given uncertain system can be easily constructed from the symmetric positive-definite solution of the associated augmented Riccati equation. The proposed approach can be applied to matched and/or mismatched systems with uncertainty matrices in which only their matrix norms are bounded by some prescribed values and/or their entries are bounded by some prescribed constraint sets. Several numerical examples are presented to illustrate the results.

Prevalence of Feeding Related Issues/Difficulties in Taiwanese Children with History of Prematurity, 2003-2006

ERIC Educational Resources Information Center

Howe, Tsu-Hsin; Hsu, Chyong-Hsin; Tsai, Mei-Wun

2010-01-01

Feeding problems are common problems seen in premature infants following their discharge from the NICU. However, the prevalence of feeding issues and failure to thrive among preterm infants in Taiwan is uncertain. All former studies of prevalence and identifications of feeding issues were from western countries. Those findings are therefore not…

Optimal Decision Making in a Class of Uncertain Systems Based on Uncertain Variables

NASA Astrophysics Data System (ADS)

Bubnicki, Z.

2006-06-01

The paper is concerned with a class of uncertain systems described by relational knowledge representations with unknown parameters which are assumed to be values of uncertain variables characterized by a user in the form of certainty distributions. The first part presents the basic optimization problem consisting in finding the decision maximizing the certainty index that the requirement given by a user is satisfied. The main part is devoted to the description of the optimization problem with the given certainty threshold. It is shown how the approach presented in the paper may be applied to some problems for anticipatory systems.

Analysis of Implicit Uncertain Systems. Part 1: Theoretical Framework

DTIC Science & Technology

1994-12-07

Analysis of Implicit Uncertain Systems Part I: Theoretical Framework Fernando Paganini * John Doyle 1 December 7, 1994 Abst rac t This paper...Analysis of Implicit Uncertain Systems Part I: Theoretical Framework 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...model and a number of constraints relevant to the analysis problem under consideration. In Part I of this paper we propose a theoretical framework which

Research of Uncertainty Reasoning in Pineapple Disease Identification System

NASA Astrophysics Data System (ADS)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

Experiences of Patients Living With Heart Failure: A Descriptive Qualitative Study.

PubMed

Seah, Alvin Chuen Wei; Tan, Khoon Kiat; Huang Gan, Juvena Chew; Wang, Wenru

2016-07-01

The purpose of this study was to explore the experiences, needs, and coping strategies of patients living with heart failure in Singapore. A descriptive qualitative design was used. A purposive sample of 15 informants was recruited from two cardiology wards of a tertiary public hospital in Singapore. Individual face-to-face interviews were conducted with a semistructured interview guideline that was developed based on a review of the literature and a pilot study. Content analysis was adopted to analyze the data, and four main categories were identified: perceived causes, manifestations, and prognosis; enduring emotions; managing the condition; and needs from health care professionals. The informants were overwhelmed with the experience of living with heart failure due to the disruptive and uncertain nature of the condition. This study offers health care professionals practical and useful suggestions when providing holistic care for patients with heart failure. © The Author(s) 2015.

Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

PubMed

Chang, Yeong-Chan

2005-12-01

This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

Missing persons-missing data: the need to collect antemortem dental records of missing persons.

PubMed

Blau, Soren; Hill, Anthony; Briggs, Christopher A; Cordner, Stephen M

2006-03-01

The subject of missing persons is of great concern to the community with numerous associated emotional, financial, and health costs. This paper examines the forensic medical issues raised by the delayed identification of individuals classified as "missing" and highlights the importance of including dental data in the investigation of missing persons. Focusing on Australia, the current approaches employed in missing persons investigations are outlined. Of particular significance is the fact that each of the eight Australian states and territories has its own Missing Persons Unit that operates within distinct state and territory legislation. Consequently, there is a lack of uniformity within Australia about the legal and procedural framework within which investigations of missing persons are conducted, and the interaction of that framework with coronial law procedures. One of the main investigative problems in missing persons investigations is the lack of forensic medical, particularly, odontological input. Forensic odontology has been employed in numerous cases in Australia where identity is unknown or uncertain because of remains being skeletonized, incinerated, or partly burnt. The routine employment of the forensic odontologist to assist in missing person inquiries, has however, been ignored. The failure to routinely employ forensic odontology in missing persons inquiries has resulted in numerous delays in identification. Three Australian cases are presented where the investigation of individuals whose identity was uncertain or unknown was prolonged due to the failure to utilize the appropriate (and available) dental resources. In light of the outcomes of these cases, we suggest that a national missing persons dental records database be established for future missing persons investigations. Such a database could be easily managed between a coronial system and a forensic medical institute. In Australia, a national missing persons dental records database could be incorporated into the National Coroners Information System (NCIS) managed, on behalf of Australia's Coroners, by the Victorian Institute of Forensic Medicine. The existence of the NCIS would ensure operational collaboration in the implementation of the system and cost savings to Australian policing agencies involved in missing person inquiries. The implementation of such a database would facilitate timely and efficient reconciliation of clinical and postmortem dental records and have subsequent social and financial benefits.

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

NASA Technical Reports Server (NTRS)

Rozier, Kristin Y.; Schumann, Johann; Ippolito, Corey

2015-01-01

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Aircraft Loss-of-Control Accident Prevention: Switching Control of the GTM Aircraft with Elevator Jam Failures

NASA Technical Reports Server (NTRS)

Chang, Bor-Chin; Kwatny, Harry G.; Belcastro, Christine; Belcastro, Celeste

2008-01-01

Switching control, servomechanism, and H2 control theory are used to provide a practical and easy-to-implement solution for the actuator jam problem. A jammed actuator not only causes a reduction of control authority, but also creates a persistent disturbance with uncertain amplitude. The longitudinal dynamics model of the NASA GTM UAV is employed to demonstrate that a single fixed reconfigured controller design based on the proposed approach is capable of accommodating an elevator jam failure with arbitrary jam position as long as the thrust control has enough control authority. This paper is a first step towards solving a more comprehensive in-flight loss-of-control accident prevention problem that involves multiple actuator failures, structure damages, unanticipated faults, and nonlinear upset regime recovery, etc.

Randomized, Controlled Trial of an Advance Care Planning Video Decision Support Tool for Patients With Advanced Heart Failure.

PubMed

El-Jawahri, Areej; Paasche-Orlow, Michael K; Matlock, Dan; Stevenson, Lynne Warner; Lewis, Eldrin F; Stewart, Garrick; Semigran, Marc; Chang, Yuchiao; Parks, Kimberly; Walker-Corkery, Elizabeth S; Temel, Jennifer S; Bohossian, Hacho; Ooi, Henry; Mann, Eileen; Volandes, Angelo E

2016-07-05

Conversations about goals of care and cardiopulmonary resuscitation (CPR)/intubation for patients with advanced heart failure can be difficult. This study examined the impact of a video decision support tool and patient checklist on advance care planning for patients with heart failure. This was a multisite, randomized, controlled trial of a video-assisted intervention and advance care planning checklist versus a verbal description in 246 patients ≥64 years of age with heart failure and an estimated likelihood of death of >50% within 2 years. Intervention participants received a verbal description for goals of care (life-prolonging care, limited care, and comfort care) and CPR/intubation plus a 6-minute video depicting the 3 levels of care, CPR/intubation, and an advance care planning checklist. Control subjects received only the verbal description. The primary analysis compared the proportion of patients preferring comfort care between study arms immediately after the intervention. Secondary outcomes were CPR/intubation preferences and knowledge (6-item test; range, 0-6) after intervention. In the intervention group, 27 (22%) chose life-prolonging care, 31 (25%) chose limited care, 63 (51%) selected comfort care, and 2 (2%) were uncertain. In the control group, 50 (41%) chose life-prolonging care, 27 (22%) selected limited care, 37 (30%) chose comfort care, and 8 (7%) were uncertain (P<0.001). Intervention participants (compared with control subjects) were more likely to forgo CPR (68% versus 35%; P<0.001) and intubation (77% versus 48%; P<0.001) and had higher mean knowledge scores (4.1 versus 3.0; P<0.001). Patients with heart failure who viewed a video were more informed, more likely to select a focus on comfort, and less likely to desire CPR/intubation compared with patients receiving verbal information only. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01589120. © 2016 American Heart Association, Inc.

Validation of accelerated ageing of Thales rotary Stirling cryocoolers for the estimation of MTTF

NASA Astrophysics Data System (ADS)

Seguineau, C.,; Cauquil, J.-M.; Martin, J.-Y.; Benschop, T.

2016-05-01

The cooled IR detectors are used in a wide range of applications. Most of the time, the cryocoolers are one of the components dimensioning the lifetime of the system. The current market needs tend to reliability figures higher than 15,000hrs in "standard conditions". Field returns are hardly useable mostly because of the uncertain environmental conditions of use, or the differences in user profiles. A previous paper explains how Thales Cryogenics has developed an approach based on accelerated ageing and statistical analysis [1]. The aim of the current paper is to compare results obtained on accelerated ageing on one side, and on the other side, specific field returns where the conditions of use are well known. The comparison between prediction and effective failure rate is discussed. Moreover, a specific focus is done on how some new applications of cryocoolers (continuous operation at a specific temperature) can increase the MTTF. Some assumptions are also exposed on how the failure modes, effects and criticality analysis evolves for continuous operation at a specific temperature and compared to experimental data.

Unbiased multi-fidelity estimate of failure probability of a free plane jet

NASA Astrophysics Data System (ADS)

Marques, Alexandre; Kramer, Boris; Willcox, Karen; Peherstorfer, Benjamin

2017-11-01

Estimating failure probability related to fluid flows is a challenge because it requires a large number of evaluations of expensive models. We address this challenge by leveraging multiple low fidelity models of the flow dynamics to create an optimal unbiased estimator. In particular, we investigate the effects of uncertain inlet conditions in the width of a free plane jet. We classify a condition as failure when the corresponding jet width is below a small threshold, such that failure is a rare event (failure probability is smaller than 0.001). We estimate failure probability by combining the frameworks of multi-fidelity importance sampling and optimal fusion of estimators. Multi-fidelity importance sampling uses a low fidelity model to explore the parameter space and create a biasing distribution. An unbiased estimate is then computed with a relatively small number of evaluations of the high fidelity model. In the presence of multiple low fidelity models, this framework offers multiple competing estimators. Optimal fusion combines all competing estimators into a single estimator with minimal variance. We show that this combined framework can significantly reduce the cost of estimating failure probabilities, and thus can have a large impact in fluid flow applications. This work was funded by DARPA.

Intelligent systems for strategic power infrastructure defense

NASA Astrophysics Data System (ADS)

Jung, Ju-Hwan

A fault or disturbance in a power system can be severe due to the sources of vulnerability such as human errors, protection and control system failures, a failure of communication networks to deliver critical control signals, and market and load uncertainties. There have been several catastrophic failures resulting from disturbances involving the sources of vulnerability while power systems are designed to withstand disturbances or faults. To avoid catastrophic failures or minimize the impact of a disturbance(s), the state of the power system has to be analyzed correctly and preventive or corrective self-healing control actions have to be deployed. This dissertation addresses two aspects of power systems: Defense system and diagnosis, both concerned with the power system analysis and operation during events involving faults or disturbances. This study is intended to develop a defense system that is able to assess power system vulnerability and to perform self-healing control actions based on the system-wide analysis. In order to meet the requirements of the system-wide analysis, the defense system is designed with multi-agent system technologies. Since power systems are dynamic and uncertain the self-healing control actions need to be adaptive. This study applies the reinforcement learning technique to provide a theoretical basis for adaptation. One of the important issues in adaptation is the convergence of the learning algorithm. An appropriate convergence criterion is derived and an application with a load-shedding scheme is demonstrated in this study. This dissertation also demonstrates the feasibility of the defense system and self-healing control actions through multi-agent system technologies. The other subject of this research is to investigate the methodology for on-line fault diagnosis using the information from Sequence-of-Events Recorders (SER). The proposed multiple-hypothesis analysis generates one or more hypothetical fault scenarios to interpret the SER information. In order to avoid ambiguity of the hypotheses, this study proposes a new method to determine the credibility of each hypothesis. Even if there is not enough SER information, the proposed method is able to perform an accurate fault and malfunction analysis. To avoid exhaustive testing, a minimal set of test scenarios is derived, which is able to handle missing information and SERs. During extreme contingencies or cascading events, fault diagnosis is the first step in the operation of the power system. On-line fault diagnosis provides necessary and correct information for the defense system to make correct and efficient decisions on self-healing control actions. It has been shown in previous studies that incorrect fault diagnosis can lead to catastrophic failures in power systems. Fault diagnosis is an important issue for strategic power infrastructure defense.

[On the recurrence risk with partial larynx resections (author's transl)].

PubMed

Flach, M

1978-06-01

28 cases of recurrences after 127 vertical and horizontal partial larynx resections (22 per cent) were analysed. Unfavourable preconditions for partial resections are the affliction of the ary cartilage and arrest of vocal chord movility. The hemiresections according to Hautant have the heighest recidivation percentage (40 per cent) judging from the observations available. Radical operations after failured partial resections are uncertain as to their prognoses.

Evaluation of Ares-I Control System Robustness to Uncertain Aerodynamics and Flex Dynamics

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; VanTassel, Chris; Bedrossian, Nazareth; Hall, Charles; Spanos, Pol

2008-01-01

This paper discusses the application of robust control theory to evaluate robustness of the Ares-I control systems. Three techniques for estimating upper and lower bounds of uncertain parameters which yield stable closed-loop response are used here: (1) Monte Carlo analysis, (2) mu analysis, and (3) characteristic frequency response analysis. All three methods are used to evaluate stability envelopes of the Ares-I control systems with uncertain aerodynamics and flex dynamics. The results show that characteristic frequency response analysis is the most effective of these methods for assessing robustness.

Bayes Analysis and Reliability Implications of Stress-Rupture Testing a Kevlar/Epoxy COPV using Temperature and Pressure Acceleration

NASA Technical Reports Server (NTRS)

Phoenix, S. Leigh; Kezirian, Michael T.; Murthy, Pappu L. N.

2009-01-01

Composite Overwrapped Pressure Vessel (COPVs) that have survived a long service time under pressure generally must be recertified before service is extended. Sometimes lifetime testing is performed on an actual COPV in service in an effort to validate the reliability model that is the basis for certifying the continued flight worthiness of its sisters. Currently, testing of such a Kevlar49(registered TradeMark)/epoxy COPV is nearing completion. The present paper focuses on a Bayesian statistical approach to analyze the possible failure time results of this test and to assess the implications in choosing between possible model parameter values that in the past have had significant uncertainty. The key uncertain parameters in this case are the actual fiber stress ratio at operating pressure, and the Weibull shape parameter for lifetime; the former has been uncertain due to ambiguities in interpreting the original and a duplicate burst test. The latter has been uncertain due to major differences between COPVs in the data base and the actual COPVs in service. Any information obtained that clarifies and eliminates uncertainty in these parameters will have a major effect on the predicted reliability of the service COPVs going forward. The key result is that the longer the vessel survives, the more likely the more optimistic stress ratio is correct. At the time of writing, the resulting effect on predicted future reliability is dramatic, increasing it by about one nine , that is, reducing the probability of failure by an order of magnitude. However, testing one vessel does not change the uncertainty on the Weibull shape parameter for lifetime since testing several would be necessary.

Stochastic unilateral free vibration of an in-plane cable network

NASA Astrophysics Data System (ADS)

Giaccu, Gian Felice; Barbiellini, Bernardo; Caracoglia, Luca

2015-03-01

Cross-ties are often used on cable-stayed bridges for mitigating wind-induced stay vibration since they can be easily installed on existing systems. The system obtained by connecting two (or more) stays with a transverse restrainer is designated as an "in-plane cable-network". Failures in the restrainers of an existing network have been observed. In a previous study [1] a model was proposed to explain the failures in the cross-ties as being related to a loss in the initial pre-tensioning force imparted to the connector. This effect leads to the "unilateral" free vibration of the network. Deterministic free vibrations of a three-cable network were investigated by using the "equivalent linearization method". Since the value of the initial vibration amplitude is often not well known due to the complex aeroelastic vibration regimes, which can be experienced by the stays, the stochastic nature of the problem must be considered. This issue is investigated in the present paper. Free-vibration dynamics of the cable network, driven by an initial stochastic disturbance associated with uncertain vibration amplitudes, is examined. The corresponding random eigen-value problem for the vibration frequencies is solved through an implementation of Stochastic Approximation, (SA) based on the Robbins-Monro Theorem. Monte-Carlo methods are also used for validating the SA results.

Reflexology has no immediate haemodynamic effect in patients with chronic heart failure: a double blind randomised controlled trial.

PubMed

Jones, Jenny; Thomson, Patricia; Lauder, William; Howie, Kate; Leslie, Stephen J

2013-08-01

This study measured the effects of reflexology in 12 reflexology-naive patients with chronic heart failure in a placebo-controlled, double blind randomised controlled study design. Outcomes included 'beat-to-beat' non-invasive continuous measurement of cardiovascular parameters and measurement of state of anxiety and pain/discomfort. There were no changes in any of the haemodynamic parameters measured (all p > 0.05). Perceived state of anxiety was significantly reduced post treatment in the control group only (p = 0.03). Reflexology applied to the feet of patients with chronic heart failure appears to have no immediate haemodynamic effects. While any long term treatment effect is uncertain, it would appear that reflexology is safe for use in this patient group. Copyright © 2013 Elsevier Ltd. All rights reserved.

Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted Euclidean distance operator

NASA Astrophysics Data System (ADS)

Liu, Hu-Chen; Liu, Long; Li, Ping

2014-10-01

Failure mode and effects analysis (FMEA) has shown its effectiveness in examining potential failures in products, process, designs or services and has been extensively used for safety and reliability analysis in a wide range of industries. However, its approach to prioritise failure modes through a crisp risk priority number (RPN) has been criticised as having several shortcomings. The aim of this paper is to develop an efficient and comprehensive risk assessment methodology using intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED) operator to overcome the limitations and improve the effectiveness of the traditional FMEA. The diversified and uncertain assessments given by FMEA team members are treated as linguistic terms expressed in intuitionistic fuzzy numbers (IFNs). Intuitionistic fuzzy weighted averaging (IFWA) operator is used to aggregate the FMEA team members' individual assessments into a group assessment. IFHWED operator is applied thereafter to the prioritisation and selection of failure modes. Particularly, both subjective and objective weights of risk factors are considered during the risk evaluation process. A numerical example for risk assessment is given to illustrate the proposed method finally.

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Current state of knowledge on Takotsubo syndrome: a Position Statement from the Taskforce on Takotsubo Syndrome of the Heart Failure Association of the European Society of Cardiology.

PubMed

Lyon, Alexander R; Bossone, Eduardo; Schneider, Birke; Sechtem, Udo; Citro, Rodolfo; Underwood, S Richard; Sheppard, Mary N; Figtree, Gemma A; Parodi, Guido; Akashi, Yoshihiro J; Ruschitzka, Frank; Filippatos, Gerasimos; Mebazaa, Alexandre; Omerovic, Elmir

2016-01-01

Takotsubo syndrome is an acute reversible heart failure syndrome that is increasingly recognized in modern cardiology practice. This Position Statement from the European Society of Cardiology Heart Failure Association provides a comprehensive review of the various clinical and pathophysiological facets of Takotsubo syndrome, including nomenclature, definition, and diagnosis, primary and secondary clinical subtypes, anatomical variants, triggers, epidemiology, pathophysiology, clinical presentation, complications, prognosis, clinical investigations, and treatment approaches. Novel structured approaches to diagnosis, risk stratification, and management are presented, with new algorithms to aid decision-making by practising clinicians. These also cover more complex areas (e.g. uncertain diagnosis and delayed presentation) and the management of complex cases with ongoing symptoms after recovery, recurrent episodes, or spontaneous presentation. The unmet needs and future directions for research in this syndrome are also discussed. © 2015 The Authors European Journal of Heart Failure © 2015 European Society of Cardiology.

Heterozygous RTEL1 variants in bone marrow failure and myeloid neoplasms

PubMed Central

Marsh, Judith C. W.; Gutierrez-Rodrigues, Fernanda; Cooper, James; Jiang, Jie; Gandhi, Shreyans; Kajigaya, Sachiko; Feng, Xingmin; Ibanez, Maria del Pilar F.; Donaires, Flávia S.; Lopes da Silva, João P.; Li, Zejuan; Das, Soma; Ibanez, Maria; Smith, Alexander E.; Lea, Nicholas; Best, Steven; Ireland, Robin; Kulasekararaj, Austin G.; McLornan, Donal P.; Pagliuca, Anthony; Callebaut, Isabelle; Young, Neal S.; Calado, Rodrigo T.; Townsley, Danielle M.

2018-01-01

Biallelic germline mutations in RTEL1 (regulator of telomere elongation helicase 1) result in pathologic telomere erosion and cause dyskeratosis congenita. However, the role of RTEL1 mutations in other bone marrow failure (BMF) syndromes and myeloid neoplasms, and the contribution of monoallelic RTEL1 mutations to disease development are not well defined. We screened 516 patients for germline mutations in telomere-associated genes by next-generation sequencing in 2 independent cohorts; one constituting unselected patients with idiopathic BMF, unexplained cytopenia, or myeloid neoplasms (n = 457) and a second cohort comprising selected patients on the basis of the suspicion of constitutional/familial BMF (n = 59). Twenty-three RTEL1 variants were identified in 27 unrelated patients from both cohorts: 7 variants were likely pathogenic, 13 were of uncertain significance, and 3 were likely benign. Likely pathogenic RTEL1 variants were identified in 9 unrelated patients (7 heterozygous and 2 biallelic). Most patients were suspected to have constitutional BMF, which included aplastic anemia (AA), unexplained cytopenia, hypoplastic myelodysplastic syndrome, and macrocytosis with hypocellular bone marrow. In the other 18 patients, RTEL1 variants were likely benign or of uncertain significance. Telomeres were short in 21 patients (78%), and 3′ telomeric overhangs were significantly eroded in 4. In summary, heterozygous RTEL1 variants were associated with marrow failure, and telomere length measurement alone may not identify patients with telomere dysfunction carrying RTEL1 variants. Pathogenicity assessment of heterozygous RTEL1 variants relied on a combination of clinical, computational, and functional data required to avoid misinterpretation of common variants. PMID:29344583

Heterozygous RTEL1 variants in bone marrow failure and myeloid neoplasms.

PubMed

Marsh, Judith C W; Gutierrez-Rodrigues, Fernanda; Cooper, James; Jiang, Jie; Gandhi, Shreyans; Kajigaya, Sachiko; Feng, Xingmin; Ibanez, Maria Del Pilar F; Donaires, Flávia S; Lopes da Silva, João P; Li, Zejuan; Das, Soma; Ibanez, Maria; Smith, Alexander E; Lea, Nicholas; Best, Steven; Ireland, Robin; Kulasekararaj, Austin G; McLornan, Donal P; Pagliuca, Anthony; Callebaut, Isabelle; Young, Neal S; Calado, Rodrigo T; Townsley, Danielle M; Mufti, Ghulam J

2018-01-09

Biallelic germline mutations in RTEL1 (regulator of telomere elongation helicase 1) result in pathologic telomere erosion and cause dyskeratosis congenita. However, the role of RTEL1 mutations in other bone marrow failure (BMF) syndromes and myeloid neoplasms, and the contribution of monoallelic RTEL1 mutations to disease development are not well defined. We screened 516 patients for germline mutations in telomere-associated genes by next-generation sequencing in 2 independent cohorts; one constituting unselected patients with idiopathic BMF, unexplained cytopenia, or myeloid neoplasms (n = 457) and a second cohort comprising selected patients on the basis of the suspicion of constitutional/familial BMF (n = 59). Twenty-three RTEL1 variants were identified in 27 unrelated patients from both cohorts: 7 variants were likely pathogenic, 13 were of uncertain significance, and 3 were likely benign. Likely pathogenic RTEL1 variants were identified in 9 unrelated patients (7 heterozygous and 2 biallelic). Most patients were suspected to have constitutional BMF, which included aplastic anemia (AA), unexplained cytopenia, hypoplastic myelodysplastic syndrome, and macrocytosis with hypocellular bone marrow. In the other 18 patients, RTEL1 variants were likely benign or of uncertain significance. Telomeres were short in 21 patients (78%), and 3' telomeric overhangs were significantly eroded in 4. In summary, heterozygous RTEL1 variants were associated with marrow failure, and telomere length measurement alone may not identify patients with telomere dysfunction carrying RTEL1 variants. Pathogenicity assessment of heterozygous RTEL1 variants relied on a combination of clinical, computational, and functional data required to avoid misinterpretation of common variants.

Fuzzy-information-based robustness of interconnected networks against attacks and failures

NASA Astrophysics Data System (ADS)

Zhu, Qian; Zhu, Zhiliang; Wang, Yifan; Yu, Hai

2016-09-01

Cascading failure is fatal in applications and its investigation is essential and therefore became a focal topic in the field of complex networks in the last decade. In this paper, a cascading failure model is established for interconnected networks and the associated data-packet transport problem is discussed. A distinguished feature of the new model is its utilization of fuzzy information in resisting uncertain failures and malicious attacks. We numerically find that the giant component of the network after failures increases with tolerance parameter for any coupling preference and attacking ambiguity. Moreover, considering the effect of the coupling probability on the robustness of the networks, we find that the robustness of the assortative coupling and random coupling of the network model increases with the coupling probability. However, for disassortative coupling, there exists a critical phenomenon for coupling probability. In addition, a critical value that attacking information accuracy affects the network robustness is observed. Finally, as a practical example, the interconnected AS-level Internet in South Korea and Japan is analyzed. The actual data validates the theoretical model and analytic results. This paper thus provides some guidelines for preventing cascading failures in the design of architecture and optimization of real-world interconnected networks.

Robust control synthesis for uncertain dynamical systems

NASA Technical Reports Server (NTRS)

Byun, Kuk-Whan; Wie, Bong; Sunkel, John

1989-01-01

This paper presents robust control synthesis techniques for uncertain dynamical systems subject to structured parameter perturbation. Both QFT (quantitative feedback theory) and H-infinity control synthesis techniques are investigated. Although most H-infinity-related control techniques are not concerned with the structured parameter perturbation, a new way of incorporating the parameter uncertainty in the robust H-infinity control design is presented. A generic model of uncertain dynamical systems is used to illustrate the design methodologies investigated in this paper. It is shown that, for a certain noncolocated structural control problem, use of both techniques results in nonminimum phase compensation.

Failing by design.

PubMed

McGrath, Rita Gunther

2011-04-01

It's hardly news that business leaders work in increasingly uncertain environments, where failures are bound to be more common than successes. Yet if you ask executives how well, on a scale of one to 10, their organizations learn from failure, you'll often get a sheepish "Two-or maybe three" in response. Such organizations are missing a big opportunity: Failure may be inevitable but, if managed well, can be very useful. A certain amount of failure can help you keep your options open, find out what doesn't work, create the conditions to attract resources and attention, make room for new leaders, and develop intuition and skill. The key to reaping these benefits is to foster "intelligent failure" throughout your organization. McGrath describes several principles that can help you put intelligent failure to work. You should decide what success and failure would look like before you start a project. Document your initial assumptions, test and revise them as you go, and convert them into knowledge. Fail fast-the longer something takes, the less you'll learn-and fail cheaply, to contain your downside risk. Limit the number of uncertainties in new projects, and build a culture that tolerates, and sometimes even celebrates, failure. Finally, codify and share what you learn. These principles won't give you a means of avoiding all failures down the road-that's simply not realistic. They will help you use small losses to attain bigger wins over time.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Sliding Mode Control of the X-33 with an Engine Failure

NASA Technical Reports Server (NTRS)

Shtessel, Yuri B.; Hall, Charles E.

2000-01-01

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Robust design of feedback feed-forward iterative learning control based on 2D system theory for linear uncertain systems

NASA Astrophysics Data System (ADS)

Li, Zhifu; Hu, Yueming; Li, Di

2016-08-01

For a class of linear discrete-time uncertain systems, a feedback feed-forward iterative learning control (ILC) scheme is proposed, which is comprised of an iterative learning controller and two current iteration feedback controllers. The iterative learning controller is used to improve the performance along the iteration direction and the feedback controllers are used to improve the performance along the time direction. First of all, the uncertain feedback feed-forward ILC system is presented by an uncertain two-dimensional Roesser model system. Then, two robust control schemes are proposed. One can ensure that the feedback feed-forward ILC system is bounded-input bounded-output stable along time direction, and the other can ensure that the feedback feed-forward ILC system is asymptotically stable along time direction. Both schemes can guarantee the system is robust monotonically convergent along the iteration direction. Third, the robust convergent sufficient conditions are given, which contains a linear matrix inequality (LMI). Moreover, the LMI can be used to determine the gain matrix of the feedback feed-forward iterative learning controller. Finally, the simulation results are presented to demonstrate the effectiveness of the proposed schemes.

Stability of uncertain impulsive complex-variable chaotic systems with time-varying delays.

PubMed

Zheng, Song

2015-09-01

In this paper, the robust exponential stabilization of uncertain impulsive complex-variable chaotic delayed systems is considered with parameters perturbation and delayed impulses. It is assumed that the considered complex-variable chaotic systems have bounded parametric uncertainties together with the state variables on the impulses related to the time-varying delays. Based on the theories of adaptive control and impulsive control, some less conservative and easily verified stability criteria are established for a class of complex-variable chaotic delayed systems with delayed impulses. Some numerical simulations are given to validate the effectiveness of the proposed criteria of impulsive stabilization for uncertain complex-variable chaotic delayed systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Uncertainty Analysis via Failure Domain Characterization: Polynomial Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Munoz, Cesar A.; Narkawicz, Anthony J.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. A Bernstein expansion approach is used to size hyper-rectangular subsets while a sum of squares programming approach is used to size quasi-ellipsoidal subsets. These methods are applicable to requirement functions whose functional dependency on the uncertainty is a known polynomial. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the uncertainty model assumed (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Adaptive identifier for uncertain complex nonlinear systems based on continuous neural networks.

PubMed

Alfaro-Ponce, Mariel; Cruz, Amadeo Argüelles; Chairez, Isaac

2014-03-01

This paper presents the design of a complex-valued differential neural network identifier for uncertain nonlinear systems defined in the complex domain. This design includes the construction of an adaptive algorithm to adjust the parameters included in the identifier. The algorithm is obtained based on a special class of controlled Lyapunov functions. The quality of the identification process is characterized using the practical stability framework. Indeed, the region where the identification error converges is derived by the same Lyapunov method. This zone is defined by the power of uncertainties and perturbations affecting the complex-valued uncertain dynamics. Moreover, this convergence zone is reduced to its lowest possible value using ideas related to the so-called ellipsoid methodology. Two simple but informative numerical examples are developed to show how the identifier proposed in this paper can be used to approximate uncertain nonlinear systems valued in the complex domain.

Robust cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain dynamics

NASA Astrophysics Data System (ADS)

Li, Keqiang; Gao, Feng; Li, Shengbo Eben; Zheng, Yang; Gao, Hongbo

2017-12-01

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range.With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

PubMed

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

Secure estimation, control and optimization of uncertain cyber-physical systems with applications to power networks

NASA Astrophysics Data System (ADS)

Taha, Ahmad Fayez

Transportation networks, wearable devices, energy systems, and the book you are reading now are all ubiquitous cyber-physical systems (CPS). These inherently uncertain systems combine physical phenomena with communication, data processing, control and optimization. Many CPSs are controlled and monitored by real-time control systems that use communication networks to transmit and receive data from systems modeled by physical processes. Existing studies have addressed a breadth of challenges related to the design of CPSs. However, there is a lack of studies on uncertain CPSs subject to dynamic unknown inputs and cyber-attacks---an artifact of the insertion of communication networks and the growing complexity of CPSs. The objective of this dissertation is to create secure, computational foundations for uncertain CPSs by establishing a framework to control, estimate and optimize the operation of these systems. With major emphasis on power networks, the dissertation deals with the design of secure computational methods for uncertain CPSs, focusing on three crucial issues---(1) cyber-security and risk-mitigation, (2) network-induced time-delays and perturbations and (3) the encompassed extreme time-scales. The dissertation consists of four parts. In the first part, we investigate dynamic state estimation (DSE) methods and rigorously examine the strengths and weaknesses of the proposed routines under dynamic attack-vectors and unknown inputs. In the second part, and utilizing high-frequency measurements in smart grids and the developed DSE methods in the first part, we present a risk mitigation strategy that minimizes the encountered threat levels, while ensuring the continual observability of the system through available, safe measurements. The developed methods in the first two parts rely on the assumption that the uncertain CPS is not experiencing time-delays, an assumption that might fail under certain conditions. To overcome this challenge, networked unknown input observers---observers/estimators for uncertain CPSs---are designed such that the effect of time-delays and cyber-induced perturbations are minimized, enabling secure DSE and risk mitigation in the first two parts. The final part deals with the extreme time-scales encompassed in CPSs, generally, and smart grids, specifically. Operational decisions for long time-scales can adversely affect the security of CPSs for faster time-scales. We present a model that jointly describes steady-state operation and transient stability by combining convex optimal power flow with semidefinite programming formulations of an optimal control problem. This approach can be jointly utilized with the aforementioned parts of the dissertation work, considering time-delays and DSE. The research contributions of this dissertation furnish CPS stakeholders with insights on the design and operation of uncertain CPSs, whilst guaranteeing the system's real-time safety. Finally, although many of the results of this dissertation are tailored to power systems, the results are general enough to be applied for a variety of uncertain CPSs.

Omega-3 Polyunsaturated Fatty Acid Supplementation to Prevent Arteriovenous Fistula and Graft Failure: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

PubMed

Viecelli, Andrea K; Irish, Ashley B; Polkinghorne, Kevan R; Hawley, Carmel M; Johnson, David W; Mori, Trevor A; Pascoe, Elaine M; Strippoli, Giovanni F M; Lok, Charmaine E; Palmer, Suetonia C

2018-07-01

Arteriovenous access failure frequently occurs in people on hemodialysis and is associated with morbidity, mortality and large healthcare expenditures. Omega-3 polyunsaturated fatty acids (omega-3 PUFA) may improve access outcomes via pleiotropic effects on access maturation and function, but may cause bleeding complications. Systematic review with meta-analysis. Adults requiring hemodialysis via arteriovenous fistula or graft. Trials evaluating omega-3 PUFA for arteriovenous access outcomes identified by searches in CENTRAL, MEDLINE, and Embase to 24 January 2017. Omega-3 PUFA. Primary patency loss, dialysis suitability failure, access abandonment, interventions to maintain patency or assist maturation, bleeding, gastrointestinal side-effects, all-cause and cardiovascular mortality, hospitalization, and treatment adherence. Treatment effects were summarized as relative risks (RR) and 95% confidence intervals (CI). Evidence was assessed using GRADE. Five eligible trials (833 participants) with a median follow-up of 12 months compared peri-operative omega-3 PUFA supplementation with placebo. One trial (n=567) evaluated treatment for fistulae and four (n=266) for grafts. Omega-3 PUFA supplementation prevented primary patency loss with moderate certainty (761 participants, RR 0.81, CI 0.68-0.98). Low quality evidence suggested, that omega-3 PUFA may have had little or no effect on dialysis suitability failure (536 participants, RR 0.95, CI 0.73-1.23), access abandonment (732 participants, RR 0.78, CI 0.59-1.03), need for interventions (732 participants, RR 0.82, CI 0.64-1.04), or all-cause mortality (799 participants, RR 0.99, CI 0.51-1.92). Bleeding risk (793 participants, RR 1.40, CI 0.78-2.49) or gastrointestinal side-effects (816 participants, RR 1.22, CI 0.64-2.34) from treatment were uncertain. There was no evidence of different treatment effects for grafts and fistulae. Small number and methodological limitations of included trials. Omega-3 PUFA supplementation probably protects against primary loss of arteriovenous access patency, but may have little or no effect on dialysis suitability failure, access interventions or access abandonment. Potential treatment harms are uncertain. Copyright © 2018 National Kidney Foundation, Inc. All rights reserved.

Effect of risk aversion on prioritizing conservation projects.

PubMed

Tulloch, Ayesha I T; Maloney, Richard F; Joseph, Liana N; Bennett, Joseph R; Di Fonzo, Martina M I; Probert, William J M; O'Connor, Shaun M; Densem, Jodie P; Possingham, Hugh P

2015-04-01

Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk--their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance-discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers' risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management framework to maximize benefits and avoid potential extinctions due to inefficient allocation of limited resources. © 2014 Society for Conservation Biology.

Terminal sliding mode tracking control for a class of SISO uncertain nonlinear systems.

PubMed

Chen, Mou; Wu, Qing-Xian; Cui, Rong-Xin

2013-03-01

In this paper, the terminal sliding mode tracking control is proposed for the uncertain single-input and single-output (SISO) nonlinear system with unknown external disturbance. For the unmeasured disturbance of nonlinear systems, terminal sliding mode disturbance observer is presented. The developed disturbance observer can guarantee the disturbance approximation error to converge to zero in the finite time. Based on the output of designed disturbance observer, the terminal sliding mode tracking control is presented for uncertain SISO nonlinear systems. Subsequently, terminal sliding mode tracking control is developed using disturbance observer technique for the uncertain SISO nonlinear system with control singularity and unknown non-symmetric input saturation. The effects of the control singularity and unknown input saturation are combined with the external disturbance which is approximated using the disturbance observer. Under the proposed terminal sliding mode tracking control techniques, the finite time convergence of all closed-loop signals are guaranteed via Lyapunov analysis. Numerical simulation results are given to illustrate the effectiveness of the proposed terminal sliding mode tracking control. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Multistage Stochastic Programming and its Applications in Energy Systems Modeling and Optimization

NASA Astrophysics Data System (ADS)

Golari, Mehdi

Electric energy constitutes one of the most crucial elements to almost every aspect of life of people. The modern electric power systems face several challenges such as efficiency, economics, sustainability, and reliability. Increase in electrical energy demand, distributed generations, integration of uncertain renewable energy resources, and demand side management are among the main underlying reasons of such growing complexity. Additionally, the elements of power systems are often vulnerable to failures because of many reasons, such as system limits, weak conditions, unexpected events, hidden failures, human errors, terrorist attacks, and natural disasters. One common factor complicating the operation of electrical power systems is the underlying uncertainties from the demands, supplies and failures of system components. Stochastic programming provides a mathematical framework for decision making under uncertainty. It enables a decision maker to incorporate some knowledge of the intrinsic uncertainty into the decision making process. In this dissertation, we focus on application of two-stage and multistage stochastic programming approaches to electric energy systems modeling and optimization. Particularly, we develop models and algorithms addressing the sustainability and reliability issues in power systems. First, we consider how to improve the reliability of power systems under severe failures or contingencies prone to cascading blackouts by so called islanding operations. We present a two-stage stochastic mixed-integer model to find optimal islanding operations as a powerful preventive action against cascading failures in case of extreme contingencies. Further, we study the properties of this problem and propose efficient solution methods to solve this problem for large-scale power systems. We present the numerical results showing the effectiveness of the model and investigate the performance of the solution methods. Next, we address the sustainability issue considering the integration of renewable energy resources into production planning of energy-intensive manufacturing industries. Recently, a growing number of manufacturing companies are considering renewable energies to meet their energy requirements to move towards green manufacturing as well as decreasing their energy costs. However, the intermittent nature of renewable energies imposes several difficulties in long term planning of how to efficiently exploit renewables. In this study, we propose a scheme for manufacturing companies to use onsite and grid renewable energies provided by their own investments and energy utilities as well as conventional grid energy to satisfy their energy requirements. We propose a multistage stochastic programming model and study an efficient solution method to solve this problem. We examine the proposed framework on a test case simulated based on a real-world semiconductor company. Moreover, we evaluate long-term profitability of such scheme via so called value of multistage stochastic programming.

Development of Probabilistic Flood Inundation Mapping For Flooding Induced by Dam Failure

NASA Astrophysics Data System (ADS)

Tsai, C.; Yeh, J. J. J.

2017-12-01

A primary function of flood inundation mapping is to forecast flood hazards and assess potential losses. However, uncertainties limit the reliability of inundation hazard assessments. Major sources of uncertainty should be taken into consideration by an optimal flood management strategy. This study focuses on the 20km reach downstream of the Shihmen Reservoir in Taiwan. A dam failure induced flood herein provides the upstream boundary conditions of flood routing. The two major sources of uncertainty that are considered in the hydraulic model and the flood inundation mapping herein are uncertainties in the dam break model and uncertainty of the roughness coefficient. The perturbance moment method is applied to a dam break model and the hydro system model to develop probabilistic flood inundation mapping. Various numbers of uncertain variables can be considered in these models and the variability of outputs can be quantified. The probabilistic flood inundation mapping for dam break induced floods can be developed with consideration of the variability of output using a commonly used HEC-RAS model. Different probabilistic flood inundation mappings are discussed and compared. Probabilistic flood inundation mappings are hoped to provide new physical insights in support of the evaluation of concerning reservoir flooded areas.

Static and dynamic efficiency of irreversible health care investments under alternative payment rules.

PubMed

Levaggi, R; Moretto, M; Pertile, P

2012-01-01

The paper studies the incentive for providers to invest in new health care technologies under alternative payment systems, when the patients' benefits are uncertain. If the reimbursement by the purchaser includes both a variable (per patient) and a lump-sum component, efficiency can be ensured both in the timing of adoption (dynamic) and the intensity of use of the technology (static). If the second instrument is unavailable, a trade-off may emerge between static and dynamic efficiency. In this context, we also discuss how the regulator could use control of the level of uncertainty faced by the provider as an instrument to mitigate the trade-off between static and dynamic efficiency. Finally, we calibrate the model to study a specific technology and estimate the cost of a regulatory failure. Copyright © 2011 Elsevier B.V. All rights reserved.

Reviews

NASA Astrophysics Data System (ADS)

2007-07-01

WE RECOMMEND God: The Failed Hypothesis A book that applies scientific logic to the search for a creator Go with the Flow This CD-ROM proves a great resource for teaching fluids Collins GCSE Student Book for EdExcel 360 Additional Science An attractive update that will sit well in modern classrooms The Rough Guide to Climate Change This book contains a thorough study of the must-teach subject InspireData Presentation software ideal for analysing data in the field WORTH A LOOK Uncertain Science...Uncertain World A book to persuade the public that unanswered questions are not a failure of science or scientists Fisher Space Pen An interesting teaching resource and a nice bit of stationery HANDLE WITH CARE Russian Space Pen A joke gift at best—no physics here IGCSE Physics for EdExcel Dull, old-fashioned approach to teaching the new qualification WEB WATCH How news headlines can prove a valuable tool to get pupils interested in a subject

A Computational Framework to Control Verification and Robustness Analysis

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2010-01-01

This paper presents a methodology for evaluating the robustness of a controller based on its ability to satisfy the design requirements. The framework proposed is generic since it allows for high-fidelity models, arbitrary control structures and arbitrary functional dependencies between the requirements and the uncertain parameters. The cornerstone of this contribution is the ability to bound the region of the uncertain parameter space where the degradation in closed-loop performance remains acceptable. The size of this bounding set, whose geometry can be prescribed according to deterministic or probabilistic uncertainty models, is a measure of robustness. The robustness metrics proposed herein are the parametric safety margin, the reliability index, the failure probability and upper bounds to this probability. The performance observed at the control verification setting, where the assumptions and approximations used for control design may no longer hold, will fully determine the proposed control assessment.

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS.

PubMed

Huang, Yi-Shao; Liu, Wel-Ping; Wu, Min; Wang, Zheng-Wu

2014-09-01

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations. Copyright © 2014. Published by Elsevier Ltd.

Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

PubMed

Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

2015-07-01

The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

Machining and grinding: High rate deformation in practice

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

Follansbee, P.S.

1993-04-01

Machining and grinding are well-established material-working operations involving highly non-uniform deformation and failure processes. A typical machining operation is characterized by uncertain boundary conditions (e.g.,surface interactions), three-dimensional stress states, large strains, high strain rates, non-uniform temperatures, highly localized deformations, and failure by both nominally ductile and brittle mechanisms. While machining and grinding are thought to be dominated by empiricism, even a cursory inspection leads one to the conclusion that this results more from necessity arising out of the complicated and highly interdisciplinary nature of the processes than from the lack thereof. With these conditions in mind, the purpose of thismore » paper is to outline the current understanding of strain rate effects in metals.« less

Machining and grinding: High rate deformation in practice

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

Follansbee, P.S.

1993-01-01

Machining and grinding are well-established material-working operations involving highly non-uniform deformation and failure processes. A typical machining operation is characterized by uncertain boundary conditions (e.g.,surface interactions), three-dimensional stress states, large strains, high strain rates, non-uniform temperatures, highly localized deformations, and failure by both nominally ductile and brittle mechanisms. While machining and grinding are thought to be dominated by empiricism, even a cursory inspection leads one to the conclusion that this results more from necessity arising out of the complicated and highly interdisciplinary nature of the processes than from the lack thereof. With these conditions in mind, the purpose of thismore » paper is to outline the current understanding of strain rate effects in metals.« less

Does Aerosol Geoengineering the Earth's Climate Pass a Cost-Benefit Test?

NASA Astrophysics Data System (ADS)

Keller, K.; Urban, N.; Tuana, N.

2007-12-01

Anthropogenic carbon dioxide (CO2) emissions are changing the Earth's climate with potentially dangerous consequences. Ratified international agreements call for a reduction of CO2 emissions to avoid dangerous anthropogenic interference with the climate system. Recent studies have, however, proposed an alternative strategy: to geoengineer Earth's climate by injecting aerosol precursors into the stratosphere. It is often claimed that aerosol geoengineering would provide net economic benefits because geoengineering requires far lower near-term investments compared to deep cuts in CO2 emissions. However, aerosol geoengineering projects can also cause nontrivial economic costs. This is because aerosol geoengineering hinges on successfully counterbalancing the forcing effects of CO2 emissions (which decay over centuries) with the forcing effects of aerosol emissions (which decay within years). A failure to maintain this delicate balance can lead to abrupt climatic changes, with potentially substantial economic damages. Deferring cuts in CO2 emissions in favor of aerosol geoengineering is hence a deeply uncertain gamble, as it requires so far unknown institutions to reliably control aerosol forcings over centuries. Here we use a simple economic model to evaluate potential costs and benefits of aerosol geoengineering for a wide range of the deeply uncertain parameters. We show that aerosol geoengineering projects may cause economic damages that can far exceed the benefits and may hence fail a cost-benefit test.

Model-based safety analysis of human-robot interactions: the MIRAS walking assistance robot.

PubMed

Guiochet, Jérémie; Hoang, Quynh Anh Do; Kaaniche, Mohamed; Powell, David

2013-06-01

Robotic systems have to cope with various execution environments while guaranteeing safety, and in particular when they interact with humans during rehabilitation tasks. These systems are often critical since their failure can lead to human injury or even death. However, such systems are difficult to validate due to their high complexity and the fact that they operate within complex, variable and uncertain environments (including users), in which it is difficult to foresee all possible system behaviors. Because of the complexity of human-robot interactions, rigorous and systematic approaches are needed to assist the developers in the identification of significant threats and the implementation of efficient protection mechanisms, and in the elaboration of a sound argumentation to justify the level of safety that can be achieved by the system. For threat identification, we propose a method called HAZOP-UML based on a risk analysis technique adapted to system description models, focusing on human-robot interaction models. The output of this step is then injected in a structured safety argumentation using the GSN graphical notation. Those approaches have been successfully applied to the development of a walking assistant robot which is now in clinical validation.

Autonomic nervous system involvement in pulmonary arterial hypertension.

PubMed

Vaillancourt, Mylène; Chia, Pamela; Sarji, Shervin; Nguyen, Jason; Hoftman, Nir; Ruffenach, Gregoire; Eghbali, Mansoureh; Mahajan, Aman; Umar, Soban

2017-12-04

Pulmonary arterial hypertension (PAH) is a chronic pulmonary vascular disease characterized by increased pulmonary vascular resistance (PVR) leading to right ventricular (RV) failure. Autonomic nervous system involvement in the pathogenesis of PAH has been demonstrated several years ago, however the extent of this involvement is not fully understood. PAH is associated with increased sympathetic nervous system (SNS) activation, decreased heart rate variability, and presence of cardiac arrhythmias. There is also evidence for increased renin-angiotensin-aldosterone system (RAAS) activation in PAH patients associated with clinical worsening. Reduction of neurohormonal activation could be an effective therapeutic strategy for PAH. Although therapies targeting adrenergic receptors or RAAS signaling pathways have been shown to reverse cardiac remodeling and improve outcomes in experimental pulmonary hypertension (PH)-models, the effectiveness and safety of such treatments in clinical settings have been uncertain. Recently, novel direct methods such as cervical ganglion block, pulmonary artery denervation (PADN), and renal denervation have been employed to attenuate SNS activation in PAH. In this review, we intend to summarize the multiple aspects of autonomic nervous system involvement in PAH and overview the different pharmacological and invasive strategies used to target autonomic nervous system for the treatment of PAH.

Performance analysis of complex repairable industrial systems using PSO and fuzzy confidence interval based methodology.

PubMed

Garg, Harish

2013-03-01

The main objective of the present paper is to propose a methodology for analyzing the behavior of the complex repairable industrial systems. In real-life situations, it is difficult to find the most optimal design policies for MTBF (mean time between failures), MTTR (mean time to repair) and related costs by utilizing available resources and uncertain data. For this, the availability-cost optimization model has been constructed for determining the optimal design parameters for improving the system design efficiency. The uncertainties in the data related to each component of the system are estimated with the help of fuzzy and statistical methodology in the form of the triangular fuzzy numbers. Using these data, the various reliability parameters, which affects the system performance, are obtained in the form of the fuzzy membership function by the proposed confidence interval based fuzzy Lambda-Tau (CIBFLT) methodology. The computed results by CIBFLT are compared with the existing fuzzy Lambda-Tau methodology. Sensitivity analysis on the system MTBF has also been addressed. The methodology has been illustrated through a case study of washing unit, the main part of the paper industry. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Life cycle assessment of overhead and underground primary power distribution.

PubMed

Bumby, Sarah; Druzhinina, Ekaterina; Feraldi, Rebe; Werthmann, Danae; Geyer, Roland; Sahl, Jack

2010-07-15

Electrical power can be distributed in overhead or underground systems, both of which generate a variety of environmental impacts at all stages of their life cycles. While there is considerable literature discussing the trade-offs between both systems in terms of aesthetics, safety, cost, and reliability, environmental assessments are relatively rare and limited to power cable production and end-of-life management. This paper assesses environmental impacts from overhead and underground medium voltage power distribution systems as they are currently built and managed by Southern California Edison (SCE). It uses process-based life cycle assessment (LCA) according to ISO 14044 (2006) and SCE-specific primary data to the extent possible. Potential environmental impacts have been calculated using a wide range of midpoint indicators, and robustness of the results has been investigated through sensitivity analysis of the most uncertain and potentially significant parameters. The studied underground system has higher environmental impacts in all indicators and for all parameter values, mostly due to its higher material intensity. For both systems and all indicators the majority of impact occurs during cable production. Promising strategies for impact reduction are thus cable failure rate reduction for overhead and cable lifetime extension for underground systems.

Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks.

PubMed

Hovakimyan, N; Nardi, F; Calise, A; Kim, Nakwan

2002-01-01

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth-order nonlinear system of relative degree two and a high-bandwidth attitude command system for a model R-50 helicopter.

River-damming, late-Quaternary rockslides in the Ötz Valley region (Tyrol, Austria)

NASA Astrophysics Data System (ADS)

Dufresne, A.; Ostermann, M.; Preusser, F.

2018-06-01

The Ötz Valley and adjacent regions in Tyrol (Austria) have been repeatedly affected by large rockslope failures following deglaciation. Six rockslides, each over 107 m3 in volume, were emplaced into the Ötz and Inn valleys, five of which formed persistent rockslide dams. Even though catastrophic rockslope failures are short-lived events (commonly minutes) they can have long-lasting impacts on the landscape. For example, large fans have built in the Ötz Valley and knickpoints persist at the former dam sites even though the Ötz River has eroded through the deposits during the past thousands of years; exact age-constraints of rockslide dam failure, however, are still scarce. Empirical, geomorphic stability indices from the literature successfully identified the least and the most stable dams of this group, whereas the rest remain inconclusive with some indices variably placing the dams in the stable, unstable, and uncertain categories. This shows (a) that further index calibrations and (b) better age constraints on dam formation and failure are needed, and (c) that the exact processes of dam failure are not always trivial to pinpoint for ancient (partially) breached dams. This study is a contribution towards better constraining the nature and landscape impact of dam formation following large rockslope failures.

Needs of caregivers in heart failure management: A qualitative study

PubMed Central

Frost, Julia; Britten, Nicky; Jolly, Kate; Greaves, Colin; Abraham, Charles; Dalal, Hayes

2015-01-01

Objectives To identify the needs of caregivers supporting a person with heart failure and to inform the development of a caregiver resource to be used as part of a home-based self-management programme. Methods A qualitative study informed by thematic analysis involving 26 caregivers in individual interviews or a focus group. Results Three distinct aspects of caregiver support in heart failure management were identified. Firstly, caregivers identified needs about supporting management of heart failure including: coping with the variability of heart failure symptoms, what to do in an emergency, understanding and managing medicines, providing emotional support, promoting exercise and physical activity, providing personal care, living with a cardiac device and supporting depression management. Secondly, as they make the transition to becoming a caregiver, they need to develop skills to undertake difficult discussions about the role; communicate with health professionals; manage their own mental health, well-being and sleep; and manage home and work. Thirdly, caregivers require skills to engage social support, and voluntary and formal services while recognising that the long-term future is uncertain. Discussion The identification of the needs of caregiver has been used to inform the development of a home-based heart failure intervention facilitated by a trained health care practitioner. PMID:25795144

Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters

NASA Astrophysics Data System (ADS)

Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei

2018-05-01

In this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.

Climate Change Impacts on Transportation; Groundwater Elevation, Road Performance, and Robust Adaptation

NASA Astrophysics Data System (ADS)

Kirshen, P. H.; Knott, J. F.; Ray, P.; Elshaer, M.; Daniel, J.; Jacobs, J. M.

2016-12-01

Transportation climate change vulnerability and adaptation studies have primarily focused on surface-water flooding from sea-level rise (SLR); little attention has been given to the effects of climate change and SLR on groundwater and subsequent impacts on the unbound foundation layers of coastal-road infrastructure. The magnitude of service-life reduction depends on the height of the groundwater in the unbound pavement materials, the pavement structure itself, and the loading. Using a steady-state groundwater model, and a multi-layer elastic pavement evaluation model, the strain changes in the layers can be determined as a function of parameter values and the strain changes translated into failure as measured by number of loading cycles to failure. For a section of a major coastal road in New Hampshire, future changes in sea-level, precipitation, temperature, land use, and groundwater pumping are characterized by deep uncertainty. Parameters that describe the groundwater system such as hydraulic conductivity can be probabilistically described while road characteristics are assumed to be deterministic. To understand the vulnerability of this road section, a bottom-up planning approach was employed over time where the combinations of parameter values that cause failure were determined and their plausibility of their occurring was analyzed. To design a robust adaptation strategy that will function reasonably well in the present and the future given the large number of uncertain parameter values, performance of adaptation options were investigated. Adaptation strategies that were considered include raising the road, load restrictions, increasing pavement layer thicknesses, replacing moisture-sensitive materials with materials that are not moisture sensitive, improving drainage systems, and treatment of the underlying materials.

Adaptive fuzzy predictive sliding control of uncertain nonlinear systems with bound-known input delay.

PubMed

Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan

2015-11-01

In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Pathology and failure in the design and implementation of adaptive management

USGS Publications Warehouse

Allen, Craig R.; Gunderson, Lance H.

2011-01-01

The conceptual underpinnings for adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex ecological systems as a result non-linear interactions among components and emergence, yet management decisions must still be made. The strength of adaptive management is in the recognition and confrontation of such uncertainty. Rather than ignore uncertainty, or use it to preclude management actions, adaptive management can foster resilience and flexibility to cope with an uncertain future, and develop safe to fail management approaches that acknowledge inevitable changes and surprises. Since its initial introduction, adaptive management has been hailed as a solution to endless trial and error approaches to complex natural resource management challenges. However, its implementation has failed more often than not. It does not produce easy answers, and it is appropriate in only a subset of natural resource management problems. Clearly adaptive management has great potential when applied appropriately. Just as clearly adaptive management has seemingly failed to live up to its high expectations. Why? We outline nine pathologies and challenges that can lead to failure in adaptive management programs. We focus on general sources of failures in adaptive management, so that others can avoid these pitfalls in the future. Adaptive management can be a powerful and beneficial tool when applied correctly to appropriate management problems; the challenge is to keep the concept of adaptive management from being hijacked for inappropriate use.

Bellman Continuum (3rd) International Workshop (13-14 June 1988)

DTIC Science & Technology

1988-06-01

Modelling Uncertain Problem ................. 53 David Bensoussan ,---,>Asymptotic Linearization of Uncertain Multivariable Systems by Sliding Modes...K. Ghosh .-. Robust Model Tracking for a Class of Singularly Perturbed Nonlinear Systems via Composite Control ....... 93 F. Garofalo and L. Glielmo...MODELISATION ET COMMANDE EN ECONOMIE MODELS AND CONTROL POLICIES IN ECONOMICS Qualitative Differential Games : A Viability Approach ............. 117

Distributed control systems with incomplete and uncertain information

NASA Astrophysics Data System (ADS)

Tang, Jingpeng

Scientific and engineering advances in wireless communication, sensors, propulsion, and other areas are rapidly making it possible to develop unmanned air vehicles (UAVs) with sophisticated capabilities. UAVs have come to the forefront as tools for airborne reconnaissance to search for, detect, and destroy enemy targets in relatively complex environments. They potentially reduce risk to human life, are cost effective, and are superior to manned aircraft for certain types of missions. It is desirable for UAVs to have a high level of intelligent autonomy to carry out mission tasks with little external supervision and control. This raises important issues involving tradeoffs between centralized control and the associated potential to optimize mission plans, and decentralized control with great robustness and the potential to adapt to changing conditions. UAV capabilities have been extended several ways through armament (e.g., Hellfire missiles on Predator UAVs), increased endurance and altitude (e.g., Global Hawk), and greater autonomy. Some known barriers to full-scale implementation of UAVs are increased communication and control requirements as well as increased platform and system complexity. One of the key problems is how UAV systems can handle incomplete and uncertain information in dynamic environments. Especially when the system is composed of heterogeneous and distributed UAVs, the overall system complexity is increased under such conditions. Presented through the use of published papers, this dissertation lays the groundwork for the study of methodologies for handling incomplete and uncertain information for distributed control systems. An agent-based simulation framework is built to investigate mathematical approaches (optimization) and emergent intelligence approaches. The first paper provides a mathematical approach for systems of UAVs to handle incomplete and uncertain information. The second paper describes an emergent intelligence approach for UAVs, again in handling incomplete and uncertain information. The third paper combines mathematical and emergent intelligence approaches.

Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems

NASA Technical Reports Server (NTRS)

Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)

2014-01-01

Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.

On-orbit servicing system assessment and optimization methods based on lifecycle simulation under mixed aleatory and epistemic uncertainties

NASA Astrophysics Data System (ADS)

Yao, Wen; Chen, Xiaoqian; Huang, Yiyong; van Tooren, Michel

2013-06-01

To assess the on-orbit servicing (OOS) paradigm and optimize its utilities by taking advantage of its inherent flexibility and responsiveness, the OOS system assessment and optimization methods based on lifecycle simulation under uncertainties are studied. The uncertainty sources considered in this paper include both the aleatory (random launch/OOS operation failure and on-orbit component failure) and the epistemic (the unknown trend of the end-used market price) types. Firstly, the lifecycle simulation under uncertainties is discussed. The chronological flowchart is presented. The cost and benefit models are established, and the uncertainties thereof are modeled. The dynamic programming method to make optimal decision in face of the uncertain events is introduced. Secondly, the method to analyze the propagation effects of the uncertainties on the OOS utilities is studied. With combined probability and evidence theory, a Monte Carlo lifecycle Simulation based Unified Uncertainty Analysis (MCS-UUA) approach is proposed, based on which the OOS utility assessment tool under mixed uncertainties is developed. Thirdly, to further optimize the OOS system under mixed uncertainties, the reliability-based optimization (RBO) method is studied. To alleviate the computational burden of the traditional RBO method which involves nested optimum search and uncertainty analysis, the framework of Sequential Optimization and Mixed Uncertainty Analysis (SOMUA) is employed to integrate MCS-UUA, and the RBO algorithm SOMUA-MCS is developed. Fourthly, a case study on the OOS system for a hypothetical GEO commercial communication satellite is investigated with the proposed assessment tool. Furthermore, the OOS system is optimized with SOMUA-MCS. Lastly, some conclusions are given and future research prospects are highlighted.

Robust Stabilization of Uncertain Systems Based on Energy Dissipation Concepts

NASA Technical Reports Server (NTRS)

Gupta, Sandeep

1996-01-01

Robust stability conditions obtained through generalization of the notion of energy dissipation in physical systems are discussed in this report. Linear time-invariant (LTI) systems which dissipate energy corresponding to quadratic power functions are characterized in the time-domain and the frequency-domain, in terms of linear matrix inequalities (LMls) and algebraic Riccati equations (ARE's). A novel characterization of strictly dissipative LTI systems is introduced in this report. Sufficient conditions in terms of dissipativity and strict dissipativity are presented for (1) stability of the feedback interconnection of dissipative LTI systems, (2) stability of dissipative LTI systems with memoryless feedback nonlinearities, and (3) quadratic stability of uncertain linear systems. It is demonstrated that the framework of dissipative LTI systems investigated in this report unifies and extends small gain, passivity, and sector conditions for stability. Techniques for selecting power functions for characterization of uncertain plants and robust controller synthesis based on these stability results are introduced. A spring-mass-damper example is used to illustrate the application of these methods for robust controller synthesis.

A robust model predictive control algorithm for uncertain nonlinear systems that guarantees resolvability

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Carson, John M., III

2006-01-01

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.

Chaos synchronization of uncertain chaotic systems using composite nonlinear feedback based integral sliding mode control.

PubMed

Mobayen, Saleh

2018-06-01

This paper proposes a combination of composite nonlinear feedback and integral sliding mode techniques for fast and accurate chaos synchronization of uncertain chaotic systems with Lipschitz nonlinear functions, time-varying delays and disturbances. The composite nonlinear feedback method allows accurate following of the master chaotic system and the integral sliding mode control provides invariance property which rejects the perturbations and preserves the stability of the closed-loop system. Based on the Lyapunov- Krasovskii stability theory and linear matrix inequalities, a novel sufficient condition is offered for the chaos synchronization of uncertain chaotic systems. This method not only guarantees the robustness against perturbations and time-delays, but also eliminates reaching phase and avoids chattering problem. Simulation results demonstrate that the suggested procedure leads to a great control performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

High-sensitivity cardiac troponin I and risk of heart failure in patients with suspected acute coronary syndrome: a cohort study.

PubMed

Stelzle, Dominik; Shah, Anoop S V; Anand, Atul; Strachan, Fiona E; Chapman, Andrew R; Denvir, Martin A; Mills, Nicholas L; McAllister, David A

2018-01-01

Heart failure may occur following acute myocardial infarction, but with the use of high-sensitivity cardiac troponin assays we increasingly diagnose patients with minor myocardial injury. Whether troponin concentrations remain a useful predictor of heart failure in patients with acute coronary syndrome is uncertain. We identified all consecutive patients (n = 4748) with suspected acute coronary syndrome (61 ± 16 years, 57% male) presenting to three secondary and tertiary care hospitals. Cox-regression models were used to evaluate the association between high-sensitivity cardiac troponin I concentration and subsequent heart failure hospitalization. C-statistics were estimated to evaluate the predictive value of troponin for heart failure hospitalization. Over 2071 years of follow-up there were 83 heart failure hospitalizations. Patients with troponin concentrations above the upper reference limit (URL) were more likely to be hospitalized with heart failure than patients below the URL (118/1000 vs. 17/1000 person years, adjusted hazard ratio: 7.0). Among patients with troponin concentrations

The Genomic Architecture of Sporadic Heart Failure

PubMed Central

Dorn, Gerald W

2011-01-01

Common or sporadic systolic heart failure (heart failure) is the clinical syndrome of insufficient forward cardiac output resulting from myocardial disease. Most heart failure is the consequence of ischemic or idiopathic cardiomyopathy. There is a clear familial predisposition to heart failure, with a genetic component estimated to confer between 20 and 30% of overall risk. The multifactorial etiology of this syndrome has complicated identification of its genetic underpinnings. Until recently, almost all genetic studies of heart failure were designed and deployed according to the common disease-common variant hypothesis, in which individual risk alleles impart a small positive or negative effect and overall genetic risk is the cumulative impact of all functional genetic variations. Early studies employed a candidate gene approach, focused mainly on factors within adrenergic and renin-angiotensin pathways that affect heart failure progression and are targeted by standard pharmacotherapeutics. Many of these reported allelic associations with heart failure have not been replicated. However, the preponderance of data support risk-modifier effects for the Arg389Gly polymorphism of β1-adrenergic receptors and the intron 16 in/del polymorphism of angiotensin converting enzyme. Recent unbiased studies using genome-wide single nucleotide polymorphism (SNP) microarrays have shown fewer positive results than when these platforms were applied to hypertension, myocardial infarction, or diabetes, possibly reflecting the complex etiology of heart failure. A new cardiovascular gene-centric sub-genome SNP array identified a common heat failure risk allele at 1p36 in multiple independent cohorts, but the biological mechanism for this association is still uncertain. It is likely that common gene polymorphisms account for only a fraction of individual genetic heart failure risk, and future studies using deep resequencing are likely to identify rare gene variants with larger biological effects. PMID:21566223

Figures of Merit for Control Verification

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Goesu. Daniel P.

2008-01-01

This paper proposes a methodology for evaluating a controller's ability to satisfy a set of closed-loop specifications when the plant has an arbitrary functional dependency on uncertain parameters. Control verification metrics applicable to deterministic and probabilistic uncertainty models are proposed. These metrics, which result from sizing the largest uncertainty set of a given class for which the specifications are satisfied, enable systematic assessment of competing control alternatives regardless of the methods used to derive them. A particularly attractive feature of the tools derived is that their efficiency and accuracy do not depend on the robustness of the controller. This is in sharp contrast to Monte Carlo based methods where the number of simulations required to accurately approximate the failure probability grows exponentially with its closeness to zero. This framework allows for the integration of complex, high-fidelity simulations of the integrated system and only requires standard optimization algorithms for its implementation.

Probabilistic liquefaction triggering based on the cone penetration test

USGS Publications Warehouse

Moss, R.E.S.; Seed, R.B.; Kayen, R.E.; Stewart, J.P.; Tokimatsu, K.

2005-01-01

Performance-based earthquake engineering requires a probabilistic treatment of potential failure modes in order to accurately quantify the overall stability of the system. This paper is a summary of the application portions of the probabilistic liquefaction triggering correlations proposed recently proposed by Moss and co-workers. To enable probabilistic treatment of liquefaction triggering, the variables comprising the seismic load and the liquefaction resistance were treated as inherently uncertain. Supporting data from an extensive Cone Penetration Test (CPT)-based liquefaction case history database were used to develop a probabilistic correlation. The methods used to measure the uncertainty of the load and resistance variables, how the interactions of these variables were treated using Bayesian updating, and how reliability analysis was applied to produce curves of equal probability of liquefaction are presented. The normalization for effective overburden stress, the magnitude correlated duration weighting factor, and the non-linear shear mass participation factor used are also discussed.

Retroperitoneal fibrosis.

PubMed

Tzou, Martha; Gazeley, David J; Mason, Peter J

2014-10-01

Retroperitoneal fibrosis (RPF) is a rare disease that is marked by systemic inflammation and the development of a periaortic fibroinflammatory mass. The fibroinflammatory infiltration can encase the abdominal aorta, ureters, and other abdominal organs. The clinical presentation often includes constitutional symptoms, abdominal pain, and signs of renal insufficiency or renal failure related to ureteral obstruction. Less frequently, RPF may present with vascular complications, such as venous thrombosis or claudication. The idiopathic form of RPF is most common but secondary forms have been described and are associated with malignancy and a variety of different medications. The pathophysiology is uncertain, but RPF has been linked with periaortitis and IgG4-related disease. Treatment centers on the relief of symptoms and complications associated with mass effects. Corticosteroids and other immunosuppressant therapies can improve constitutional symptoms, reduce infiltrate mass, and achieve disease remission, but a chronic relapsing course is not uncommon. © The Author(s) 2014.

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

NASA Technical Reports Server (NTRS)

Gaebler, John A.; Tolson, Robert H.

2010-01-01

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

Does load-induced ventricular hypertrophy progress to systolic heart failure?

PubMed

Berenji, Kambeez; Drazner, Mark H; Rothermel, Beverly A; Hill, Joseph A

2005-07-01

Ventricular hypertrophy develops in response to numerous forms of cardiac stress, including pressure or volume overload, loss of contractile mass from prior infarction, neuroendocrine activation, and mutations in genes encoding sarcomeric proteins. Hypertrophic growth is believed to have a compensatory role that diminishes wall stress and oxygen consumption, but Framingham and other studies established ventricular hypertrophy as a marker for increased risk of developing chronic heart failure, suggesting that hypertrophy may have maladaptive features. However, the relative contribution of comorbid disease to hypertrophy-associated systolic failure is unknown. For instance, coronary artery disease is induced by many of the same risk factors that cause hypertrophy and can itself lead to systolic dysfunction. It is uncertain, therefore, whether ventricular hypertrophy commonly progresses to systolic dysfunction without the contribution of intervening ischemia or infarction. In this review, we summarize findings from epidemiologic studies, preclinical experiments in animals, and clinical trials to lay out what is known-and not known-about this important question.

When does ecological sustainability ensure economic sustainability? An integrated analysis of thresholds in semi-arid western rangelands

NASA Astrophysics Data System (ADS)

Cobourn, K. M.; Peckham, S. D.

2011-12-01

The vulnerability of agri-environmental systems to ecological threshold events depends on the combined influence of economic factors and natural drivers, such as climate and disturbance. This analysis builds an integrated ecologic-economic model to evaluate the behavioral response of agricultural producers to changing and uncertain natural conditions. The model explicitly reflects the effect of producer behavior on the likelihood of a threshold event that threatens the ecological and/or economic sustainability of the agri-environmental system. The foundation of the analysis is a threshold indicator that incorporates the population dynamics of a species that supports economic production and an episodic disturbance regime-in this case rangeland grass that is grazed by livestock and is subject to wildfire. This ecological indicator is integrated into an economic model in which producers choose grazing intensity given the state of the grass population and a set of economic parameters. We examine two model variants that characterize differing economic circumstances. The first characterizes the optimal grazing regime assuming that the system is managed by a single planner whose objective is to maximize the aggregate long-run returns of producers in the system. The second examines the case in which individual producers choose their own stocking rates in order to maximize their private economic benefit. The results from the first model variant illustrate the difference between an ecologic and an economic threshold. Failure to cross an ecological threshold does not necessarily ensure that the system remains economically viable: Economic sustainability, defined as the ability of the system to support optimal production into the infinite future, requires that the net growth rate of the supporting population exceeds the level required for ecological sustainability by an amount that depends on the market price of livestock and grazing efficiency. The results from the second model variant define the circumstances under which a system that is otherwise ecologically sustainable is driven over a threshold by the actions of economic agents. The difference between the two model solutions identifies bounds between which the viability of livestock production over the long-run is uncertain and depends upon the policy setting in which the agri-environmental system operates.

Development of a structural health monitoring system for the life assessment of critical transportation infrastructure.

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

Roach, Dennis Patrick; Jauregui, David Villegas; Daumueller, Andrew Nicholas

2012-02-01

Recent structural failures such as the I-35W Mississippi River Bridge in Minnesota have underscored the urgent need for improved methods and procedures for evaluating our aging transportation infrastructure. This research seeks to develop a basis for a Structural Health Monitoring (SHM) system to provide quantitative information related to the structural integrity of metallic structures to make appropriate management decisions and ensuring public safety. This research employs advanced structural analysis and nondestructive testing (NDT) methods for an accurate fatigue analysis. Metal railroad bridges in New Mexico will be the focus since many of these structures are over 100 years old andmore » classified as fracture-critical. The term fracture-critical indicates that failure of a single component may result in complete collapse of the structure such as the one experienced by the I-35W Bridge. Failure may originate from sources such as loss of section due to corrosion or cracking caused by fatigue loading. Because standard inspection practice is primarily visual, these types of defects can go undetected due to oversight, lack of access to critical areas, or, in riveted members, hidden defects that are beneath fasteners or connection angles. Another issue is that it is difficult to determine the fatigue damage that a structure has experienced and the rate at which damage is accumulating due to uncertain history and load distribution in supporting members. A SHM system has several advantages that can overcome these limitations. SHM allows critical areas of the structure to be monitored more quantitatively under actual loading. The research needed to apply SHM to metallic structures was performed and a case study was carried out to show the potential of SHM-driven fatigue evaluation to assess the condition of critical transportation infrastructure and to guide inspectors to potential problem areas. This project combines the expertise in transportation infrastructure at New Mexico State University with the expertise at Sandia National Laboratories in the emerging field of SHM.« less

Robust preview control for a class of uncertain discrete-time systems with time-varying delay.

PubMed

Li, Li; Liao, Fucheng

2018-02-01

This paper proposes a concept of robust preview tracking control for uncertain discrete-time systems with time-varying delay. Firstly, a model transformation is employed for an uncertain discrete system with time-varying delay. Then, the auxiliary variables related to the system state and input are introduced to derive an augmented error system that includes future information on the reference signal. This leads to the tracking problem being transformed into a regulator problem. Finally, for the augmented error system, a sufficient condition of asymptotic stability is derived and the preview controller design method is proposed based on the scaled small gain theorem and linear matrix inequality (LMI) technique. The method proposed in this paper not only solves the difficulty problem of applying the difference operator to the time-varying matrices but also simplifies the structure of the augmented error system. The numerical simulation example also illustrates the effectiveness of the results presented in the paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Effective production planning for purchased part under long lead time and uncertain demand: MRP Vs demand-driven MRP

NASA Astrophysics Data System (ADS)

Shofa, M. J.; Moeis, A. O.; Restiana, N.

2018-04-01

MRP as a production planning system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic, so that MRP is inappropriate at the time. Demand-Driven MRP (DDMRP) is new approach for production planning system dealing with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP for purchased part under long lead time and uncertain demand in terms of average inventory levels. The evaluation is conducted through a discrete event simulation with the long lead time and uncertain demand scenarios. The next step is evaluating the performance of DDMRP by comparing the inventory level of DDMRP with MRP. As result, DDMRP is more effective production planning than MRP in terms of average inventory levels.

Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces

NASA Astrophysics Data System (ADS)

Song, Qi; Song, Y. D.; Cai, Wenchuan

2011-09-01

Although backstepping control design approach has been widely utilised in many practical systems, little effort has been made in applying this useful method to train systems. The main purpose of this paper is to apply this popular control design technique to speed and position tracking control of high-speed trains. By integrating adaptive control with backstepping control, we develop a control scheme that is able to address not only the traction and braking dynamics ignored in most existing methods, but also the uncertain friction and aerodynamic drag forces arisen from uncertain resistance coefficients. As such, the resultant control algorithms are able to achieve high precision train position and speed tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations.

Robust linear quadratic designs with respect to parameter uncertainty

NASA Technical Reports Server (NTRS)

Douglas, Joel; Athans, Michael

1992-01-01

The authors derive a linear quadratic regulator (LQR) which is robust to parametric uncertainty by using the overbounding method of I. R. Petersen and C. V. Hollot (1986). The resulting controller is determined from the solution of a single modified Riccati equation. It is shown that, when applied to a structural system, the controller gains add robustness by minimizing the potential energy of uncertain stiffness elements, and minimizing the rate of dissipation of energy through uncertain damping elements. A worst-case disturbance in the direction of the uncertainty is also considered. It is proved that performance robustness has been increased with the robust LQR when compared to a mismatched LQR design where the controller is designed on the nominal system, but applied to the actual uncertain system.

The in-flight performance of the Solar Maximum Mission Electrical Power System

NASA Technical Reports Server (NTRS)

Broderick, R. J.

1981-01-01

Circuitry, power handling, and operational characteristics and anomalies of the Electrical Power System (EPS) of the Solar Maximum Mission are discussed. The EPS is designed as a standard unit to be a candidate for use on future space missions. Blown, improperly derated fuses in the Attitude Control System and the Signal Conditioning Assembly have led to switching to magnetrons for solar angle, with a loss of accuracy, and a loss of one-half of telemetry data, respectively. In addition, reasons for an 11-14% degradation of solar array output are uncertain due to the loss of precise attitude control. Current surges to peak at 76.5 A (down from 94.5 A) at sunrise, stays for four to five minutes, then resumes nominal output for the remainder of the 61-68 daytime period. Eclipse varies between 28 and 35 minutes, with corresponding depth of discharge of 14%. The batteries charge at 20 A, and although an overcharge mode has been continuously sensed, operation has been normal and temperature sensors have not indicated overcharge; cell failure has also not been sensed. The system has a two year design life and a desired life of four years.

Shifting and Sharing: Academic Physicians' Strategies for Navigating Underperformance and Failure.

PubMed

LaDonna, Kori A; Ginsburg, Shiphra; Watling, Christopher

2018-05-22

Medical practice is uncertain and complex. Consequently, even outstanding performers will inevitably experience moments of underperformance and failure. Coping relies on insight and resilience. However, how physicians develop and use these skills to navigate struggle remains underexplored. A better understanding may reveal strategies to support both struggling learners and stressed practitioners. In 2015, 28 academic physicians were interviewed about their experiences with underperformance or failure. Constructivist grounded theory informed data collection and analysis. Participants' experiences with struggle ranged from patient errors and academic failures to frequent, smaller moments of interpersonal conflict and work-life imbalance. To buffer impact, participants sometimes shifted their focus to an aspect of their identity where they felt successful. Additionally, while participants perceived that insight develops by acknowledging and reflecting on error, they sometimes deflected blame for performance gaps. More often, participants seemed to accept personal responsibility while simultaneously sharing accountability for underperformance or failure with external forces. Paradoxically, participants perceived learners who used these strategies as lacking in insight. Participants demonstrated the protective and functional value of distributing responsibility for underperformance and failure. Shifting and sharing may be an element of reflection and resilience; recognizing external factors may provide a way to gain perspective and to preserve the self. However, this strategy challenges educators' assumptions that learners who deflect are avoiding personal responsibility. The authors' findings raise questions about what it means to be resilient, and how assumptions about learners' responses to failure may affect strategies to support underperforming learners.

A recursive Bayesian approach for fatigue damage prognosis: An experimental validation at the reliability component level

NASA Astrophysics Data System (ADS)

Gobbato, Maurizio; Kosmatka, John B.; Conte, Joel P.

2014-04-01

Fatigue-induced damage is one of the most uncertain and highly unpredictable failure mechanisms for a large variety of mechanical and structural systems subjected to cyclic and random loads during their service life. A health monitoring system capable of (i) monitoring the critical components of these systems through non-destructive evaluation (NDE) techniques, (ii) assessing their structural integrity, (iii) recursively predicting their remaining fatigue life (RFL), and (iv) providing a cost-efficient reliability-based inspection and maintenance plan (RBIM) is therefore ultimately needed. In contribution to these objectives, the first part of the paper provides an overview and extension of a comprehensive reliability-based fatigue damage prognosis methodology — previously developed by the authors — for recursively predicting and updating the RFL of critical structural components and/or sub-components in aerospace structures. In the second part of the paper, a set of experimental fatigue test data, available in the literature, is used to provide a numerical verification and an experimental validation of the proposed framework at the reliability component level (i.e., single damage mechanism evolving at a single damage location). The results obtained from this study demonstrate (i) the importance and the benefits of a nearly continuous NDE monitoring system, (ii) the efficiency of the recursive Bayesian updating scheme, and (iii) the robustness of the proposed framework in recursively updating and improving the RFL estimations. This study also demonstrates that the proposed methodology can lead to either an extent of the RFL (with a consequent economical gain without compromising the minimum safety requirements) or an increase of safety by detecting a premature fault and therefore avoiding a very costly catastrophic failure.

Intergovernmental relations and Long Term Care reforms: lessons from the Italian case.

PubMed

Gabriele, Stefania; Tediosi, Fabrizio

2014-05-01

The article aims at analysing the reasons why Italy failed to reform Long Term Care (LTC) policies, focusing on an aspect which has been overlooked: the interplay between LTC policies and the intergovernmental multilevel relationships. In the Italian LTC system, the main central intervention has been the regularisation of migrant care work, while the automatic growth of the cash benefits has accompanied the care needs evolution. Therefore the only institutional change has been a "gradual transformation". The causes of the failure to reform LTC have been mainly related to a strong fragmentation of the policy field, the existence of a universalistic cash benefit, the fiscal constraint. We argue that a further obstacle to reform LTC policies has been the weak and uncertain legislative framework of federalism. The uncertainty on the allocation and distribution of resources and the delay to apply the equalisation mechanism based on needs engendered a lame federalism that contributed to hindering welfare innovations and to increasing the institutional fragmentation. The analysis is partly consistent with previous literature, although it places less emphasis on the role of the constituencies and the scarcity of resources in influencing decisions, focusing more on the implications of the failure to fully realise the federalist reform. This focus shows that to implement institutional change in the welfare system, it is important to take into account the features of the federal governance, the intergovernmental relations, and to address the challenges that are connected to them. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Adaptive Optimal Control Using Frequency Selective Information of the System Uncertainty With Application to Unmanned Aircraft.

PubMed

Maity, Arnab; Hocht, Leonhard; Heise, Christian; Holzapfel, Florian

2018-01-01

A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input effectiveness failures or damages. For adaptation of the unknown parameters of these uncertainties, the frequency selective learning approach is used. Its idea is to compute a filtered expression of the system uncertainty using multiple filters based on online instantaneous information, which is used for augmentation of the update law. It is capable of adjusting a sudden change in system dynamics without depending on high adaptation gains and can satisfy exponential parameter error convergence under certain conditions in the presence of structured matched and unmatched uncertainties as well. Additionally, the controller of the MRAC system is designed using a new optimal control method. This method is a new linear quadratic regulator-based optimal control formulation for both output regulation and command tracking problems. It provides a closed-form control solution. The proposed overall approach is applied in a control of lateral dynamics of an unmanned aircraft problem to show its effectiveness.

Heart failure: a weak link in CHA2 DS2 -VASc.

PubMed

Friberg, Leif; Lund, Lars H

2018-06-01

In atrial fibrillation, stroke risk is assessed by the CHA 2 DS 2 -VASc score. Heart failure is included in CHA 2 DS 2 -VASc, but the rationale is uncertain. Our objective was to test if heart failure is a risk factor for stroke, independent of other risk factors in CHA 2 DS 2 -VASc. We studied 300 839 patients with atrial fibrillation in the Swedish Patient Register 2005-11. Three definitions of heart failure were used in order to assess the robustness of the results. In the main analysis, heart failure was defined by a hospital discharge diagnosis of heart failure as first or second diagnosis and a filled prescription of a diuretic within 3 months before index + 30 days. The second definition counted first or second discharge diagnoses <1 year before index + 30 days and the third definition any heart failure diagnosis in open or hospital care before index + 30 days. Associations with outcomes were assessed with multivariable Cox analyses. Patients with heart failure were older (80.5 vs. 74.0 years, P < 0.001) and had higher CHA 2 DS 2 -VASc score (4.4 vs. 2.7, P < 0.001). The 1 year incidence of ischaemic stroke without warfarin was 4.4% with heart failure and 3.1% without. Adjustment for the cofactors in CHA 2 DS 2 -VASc eradicated the difference in stroke risk between patients with and without heart failure (hazard ratio 1.01 with 95% confidence interval 0.96-1.05). The area under the receiver operating characteristic curve for CHA 2 DS 2 -VASc was not improved by points for heart failure. A clinical diagnosis of heart failure was not an independent risk factor for stroke in patients with atrial fibrillation, which may have implications for anticoagulation management. © 2018 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of the European Society of Cardiology.

Control of Uncertain Systems under Constraints: Switching Horizon Predictive Control of Persistently Disturbed Input-Saturated Plants

DTIC Science & Technology

2006-12-01

on at any time from a family of candidate feedback-gains so as to control a discrete- time input-saturated LTI system possibly subject to persistent... times robustness Mosca, E. (2006) Control of Uncertain Systems under Constraints: Switching Horizon Predictive Control of Persistently Disturbed...feedback controls u = f(x̂) (3) so as to ensure, under suitable conditions, stability in the noiseless case as well as finite l∞-induced gain of the

Increase in hospital admission rates for heart failure in The Netherlands, 1980-1993.

PubMed Central

Reitsma, J. B.; Mosterd, A.; de Craen, A. J.; Koster, R. W.; van Capelle, F. J.; Grobbee, D. E.; Tijssen, J. G.

1996-01-01

OBJECTIVE: To study the trend in hospital admission rates for heart failure in the Netherlands from 1980 to 1993. DESIGN: All hospital admissions in the Netherlands with a principal discharge diagnosis of heart failure were analysed. In addition, individual records of heart failure patients from a subset of 7 hospitals were analysed to estimate the frequency and timing of readmissions. RESULTS: The total number of discharges for men increased from 7377 in 1980 to 13 022 in 1993, and for women from 7064 to 12 944. From 1980 through 1993 age adjusted discharge rates rose 48% for men and 40% for women. Age adjusted in-hospital mortality for heart failure decreased from 19% in 1980 to 15% in 1993. For all age groups in-hospital mortality for men was higher than for women. The mean length of hospital admissions in 1993 was 14.0 days for men and 16.4 days for women. A review of individual patient records from a 6.3% sample of all hospital admissions in the Netherlands indicated that within a 2 year period 18% of the heart failure patients were admitted more than once and 5% more than twice. CONCLUSIONS: For both men and women a pronounced increase in age adjusted discharge rates for heart failure was observed in the Netherlands from 1980 to 1993. Readmissions were a prominent feature among heart failure patients. Higher survival rates after acute myocardial infarction and the longer survival of patients with heart disease, including heart failure may have contributed to the observed increase. The importance of advances in diagnostic tools and of possible changes in admission policy remain uncertain. PMID:8944582

Hard and Soft Constraints in Reliability-Based Design Optimization

NASA Technical Reports Server (NTRS)

Crespo, L.uis G.; Giesy, Daniel P.; Kenny, Sean P.

2006-01-01

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

Fear and Trembling: Hong Kong Librarians Face Their Uncertain Future.

ERIC Educational Resources Information Center

Chepesiuk, Ron

1992-01-01

Discussion of the possible changes in Hong Kong in 1997 when rule passes to the People's Republic of China focuses on the uncertain future of libraries and librarians. Topics discussed include the political climate; the departure of qualified Chinese librarians; and the growth of libraries and computerized systems. (LRW)

Neural-network-based online HJB solution for optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems.

PubMed

Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong

2014-12-01

In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.

Robust stabilization of the Space Station in the presence of inertia matrix uncertainty

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang; Sunkel, John

1993-01-01

This paper presents a robust H-infinity full-state feedback control synthesis method for uncertain systems with D11 not equal to 0. The method is applied to the robust stabilization problem of the Space Station in the face of inertia matrix uncertainty. The control design objective is to find a robust controller that yields the largest stable hypercube in uncertain parameter space, while satisfying the nominal performance requirements. The significance of employing an uncertain plant model with D11 not equal 0 is demonstrated.

Inability to determine tissue health is main indication of allograft use in intermediate extent burns.

PubMed

Fletcher, John L; Cancio, Leopoldo C; Sinha, Indranil; Leung, Kai P; Renz, Evan M; Chan, Rodney K

2015-12-01

Cutaneous allograft is commonly used in the early coverage of excised burns when autograft is unavailable. However, allograft is also applied in intermediate-extent burns (25-50%), during cases in which it is possible to autograft. In this population, there is a paucity of data on the indications for allograft use. This study explores the indications for allograft usage in moderate size burns. Under an IRB-approved protocol, patients admitted to our burn unit between March 2003 and December 2010 were identified through a review of the burn registry. Data on allograft use, total burn surface area, operation performed, operative intent, number of operations, intensive care unit length of stay, and overall length of stay were collected and analyzed. Data are presented as means±standard deviations, except where noted. In the study period, 146 patients received allograft during their acute hospitalization. Twenty-five percent of allograft recipients sustained intermediate-extent burns. Patients with intermediate-extent burns received allograft later in their hospitalization than those with large-extent (50-75% TBSA) burns (6.8 days vs. 3.4 days, p=0.01). Allografted patients with intermediate-extent burns underwent more operations (10.8 vs. 6.1, p=0.002) and had longer hospitalizations (78.3 days vs. 40.9 days, p<0.001) than non-allografted patients, when controlled for TBSA. Clinical rationale for placement of allograft in this population included autograft failure, uncertain depth of excision, lack of autograft donor site, and wound complexity. When uncertain depth of excision was the indication, allograft was universally applied onto the face. In half of allografted intermediate-extent burn patients the inability to identify a viable recipient bed was the ultimate reason for allograft use. Unlike large body surface area burns, allograft skin use in intermediate-extent injury occurs later in the hospitalization and is driven by the inability to determine wound bed suitability for autograft application. Allograft application can be utilized to test recipient site viability in cases of autograft failure or uncertain depth of excision. Published by Elsevier Ltd.

A new smooth robust control design for uncertain nonlinear systems with non-vanishing disturbances

NASA Astrophysics Data System (ADS)

Xian, Bin; Zhang, Yao

2016-06-01

In this paper, we consider the control problem for a general class of nonlinear system subjected to uncertain dynamics and non-varnishing disturbances. A smooth nonlinear control algorithm is presented to tackle these uncertainties and disturbances. The proposed control design employs the integral of a nonlinear sigmoid function to compensate the uncertain dynamics, and achieve a uniformly semi-global practical asymptotic stable tracking control of the system outputs. A novel Lyapunov-based stability analysis is employed to prove the convergence of the tracking errors and the stability of the closed-loop system. Numerical simulation results on a two-link robot manipulator are presented to illustrate the performance of the proposed control algorithm comparing with the layer-boundary sliding mode controller and the robust of integration of sign of error control design. Furthermore, real-time experiment results for the attitude control of a quadrotor helicopter are also included to confirm the effectiveness of the proposed algorithm.

Identification of failure type in corroded pipelines: a bayesian probabilistic approach.

PubMed

Breton, T; Sanchez-Gheno, J C; Alamilla, J L; Alvarez-Ramirez, J

2010-07-15

Spillover of hazardous materials from transport pipelines can lead to catastrophic events with serious and dangerous environmental impact, potential fire events and human fatalities. The problem is more serious for large pipelines when the construction material is under environmental corrosion conditions, as in the petroleum and gas industries. In this way, predictive models can provide a suitable framework for risk evaluation, maintenance policies and substitution procedure design that should be oriented to reduce increased hazards. This work proposes a bayesian probabilistic approach to identify and predict the type of failure (leakage or rupture) for steel pipelines under realistic corroding conditions. In the first step of the modeling process, the mechanical performance of the pipe is considered for establishing conditions under which either leakage or rupture failure can occur. In the second step, experimental burst tests are used to introduce a mean probabilistic boundary defining a region where the type of failure is uncertain. In the boundary vicinity, the failure discrimination is carried out with a probabilistic model where the events are considered as random variables. In turn, the model parameters are estimated with available experimental data and contrasted with a real catastrophic event, showing good discrimination capacity. The results are discussed in terms of policies oriented to inspection and maintenance of large-size pipelines in the oil and gas industry. 2010 Elsevier B.V. All rights reserved.

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

Zhang, Jiangjiang; Li, Weixuan; Lin, Guang

In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters.more » To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.« less

Prediction-based control for LTI systems with uncertain time-varying delays and partial state knowledge

NASA Astrophysics Data System (ADS)

Léchappé, V.; Moulay, E.; Plestan, F.

2018-06-01

The stability of a prediction-based controller for linear time-invariant (LTI) systems is studied in the presence of time-varying input and output delays. The uncertain delay case is treated as well as the partial state knowledge case. The reduction method is used in order to prove the convergence of the closed-loop system including the state observer, the predictor and the plant. Explicit conditions that guarantee the closed-loop stability are given, thanks to a Lyapunov-Razumikhin analysis. Simulations illustrate the theoretical results.

Recombinant glucagon-like peptide-1 increases myocardial glucose uptake and improves left ventricular performance in conscious dogs with pacing-induced dilated cardiomyopathy.

PubMed

Nikolaidis, Lazaros A; Elahi, Dariush; Hentosz, Teresa; Doverspike, Aaron; Huerbin, Rhonda; Zourelias, Lee; Stolarski, Carol; Shen, You-tang; Shannon, Richard P

2004-08-24

The failing heart demonstrates a preference for glucose as its metabolic substrate. Whether enhancing myocardial glucose uptake favorably influences left ventricular (LV) contractile performance in heart failure remains uncertain. Glucagon-like peptide-1 (GLP-1) is a naturally occurring incretin with potent insulinotropic effects the action of which is attenuated when glucose levels fall below 4 mmol. We examined the impact of recombinant GLP-1 (rGLP-1) on LV and systemic hemodynamics and myocardial substrate uptake in conscious dogs with advanced dilated cardiomyopathy (DCM) as a mechanism for overcoming myocardial insulin resistance and enhancing myocardial glucose uptake. Thirty-five dogs were instrumented and studied in the fully conscious state. Advanced DCM was induced by 28 days of rapid pacing. Sixteen dogs with advanced DCM received a 48-hour infusion of rGLP-1 (1.5 pmol x kg(-1) x min(-1)). Eight dogs with DCM served as controls and received 48 hours of a saline infusion (3 mL/d). Infusion of rGLP-1 was associated with significant (P<0.02) increases in LV dP/dt (98%), stroke volume (102%), and cardiac output (57%) and significant decreases in LV end-diastolic pressure, heart rate, and systemic vascular resistance. rGLP-1 increased myocardial insulin sensitivity and myocardial glucose uptake. There were no significant changes in the saline control group. rGLP-1 dramatically improved LV and systemic hemodynamics in conscious dogs with advanced DCM induced by rapid pacing. rGLP-1 has insulinomimetic and glucagonostatic properties, with resultant increases in myocardial glucose uptake. rGLP-1 may be a useful metabolic adjuvant in decompensated heart failure.

Algorithms for sum-of-squares-based stability analysis and control design of uncertain nonlinear systems

NASA Astrophysics Data System (ADS)

Ataei-Esfahani, Armin

In this dissertation, we present algorithmic procedures for sum-of-squares based stability analysis and control design for uncertain nonlinear systems. In particular, we consider the case of robust aircraft control design for a hypersonic aircraft model subject to parametric uncertainties in its aerodynamic coefficients. In recent years, Sum-of-Squares (SOS) method has attracted increasing interest as a new approach for stability analysis and controller design of nonlinear dynamic systems. Through the application of SOS method, one can describe a stability analysis or control design problem as a convex optimization problem, which can efficiently be solved using Semidefinite Programming (SDP) solvers. For nominal systems, the SOS method can provide a reliable and fast approach for stability analysis and control design for low-order systems defined over the space of relatively low-degree polynomials. However, The SOS method is not well-suited for control problems relating to uncertain systems, specially those with relatively high number of uncertainties or those with non-affine uncertainty structure. In order to avoid issues relating to the increased complexity of the SOS problems for uncertain system, we present an algorithm that can be used to transform an SOS problem with uncertainties into a LMI problem with uncertainties. A new Probabilistic Ellipsoid Algorithm (PEA) is given to solve the robust LMI problem, which can guarantee the feasibility of a given solution candidate with an a-priori fixed probability of violation and with a fixed confidence level. We also introduce two approaches to approximate the robust region of attraction (RROA) for uncertain nonlinear systems with non-affine dependence on uncertainties. The first approach is based on a combination of PEA and SOS method and searches for a common Lyapunov function, while the second approach is based on the generalized Polynomial Chaos (gPC) expansion theorem combined with the SOS method and searches for parameter-dependent Lyapunov functions. The control design problem is investigated through a case study of a hypersonic aircraft model with parametric uncertainties. Through time-scale decomposition and a series of function approximations, the complexity of the aircraft model is reduced to fall within the capability of SDP solvers. The control design problem is then formulated as a convex problem using the dual of the Lyapunov theorem. A nonlinear robust controller is searched using the combined PEA/SOS method. The response of the uncertain aircraft model is evaluated for two sets of pilot commands. As the simulation results show, the aircraft remains stable under up to 50% uncertainty in aerodynamic coefficients and can follow the pilot commands.

Erlotinib Versus Radiation Therapy for Brain Metastases in Patients With EGFR-Mutant Lung Adenocarcinoma

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

Gerber, Naamit K.; Yamada, Yoshiya; Rimner, Andreas

2014-06-01

Purpose/Objectives: Radiation therapy (RT) is the principal modality in the treatment of patients with brain metastases (BM). However, given the activity of EGFR tyrosine kinase inhibitors in the central nervous system, it is uncertain whether upfront brain RT is necessary for patients with EGFR-mutant lung adenocarcinoma with BM. Methods and Materials: Patients with EGFR-mutant lung adenocarcinoma and newly diagnosed BM were identified. Results: 222 patients were identified. Exclusion criteria included prior erlotinib use, presence of a de novo erlotinib resistance mutation, or incomplete data. Of the remaining 110 patients, 63 were treated with erlotinib, 32 with whole brain RT (WBRT), andmore » 15 with stereotactic radiosurgery (SRS). The median overall survival (OS) for the whole cohort was 33 months. There was no significant difference in OS between the WBRT and erlotinib groups (median, 35 vs 26 months; P=.62), whereas patients treated with SRS had a longer OS than did those in the erlotinib group (median, 64 months; P=.004). The median time to intracranial progression was 17 months. There was a longer time to intracranial progression in patients who received WBRT than in those who received erlotinib upfront (median, 24 vs 16 months, P=.04). Patients in the erlotinib or SRS group were more likely to experience intracranial failure as a component of first failure, whereas WBRT patients were more likely to experience failure outside the brain (P=.004). Conclusions: The survival of patients with EGFR-mutant adenocarcinoma with BM is notably long, whether they receive upfront erlotinib or brain RT. We observed longer intracranial control with WBRT, even though the WBRT patients had a higher burden of intracranial disease. Despite the equivalent survival between the WBRT and erlotinib group, this study underscores the role of WBRT in producing durable intracranial control in comparison with a targeted biologic agent with known central nervous system activity.« less

Dysregulated endocardial TGFβ signaling and mesenchymal transformation result in heart outflow tract septation failure.

PubMed

Ma, Mancheong; Li, Peng; Shen, Hua; Estrada, Kristine D; Xu, Jian; Kumar, S Ram; Sucov, Henry M

2016-01-01

Heart outflow tract septation in mouse embryos carrying mutations in retinoic acid receptor genes fails with complete penetrance. In this mutant background, ectopic TGFβ signaling in the distal outflow tract is responsible for septation failure, but it was uncertain what tissue was responsive to ectopic TGFβ and why this response interfered with septation. By combining RAR gene mutation with tissue-specific Cre drivers and a conditional type II TGFβ receptor (Tgfbr2) allele, we determined that ectopic activation of TGFβ signaling in the endocardium is responsible for septation defects. Ectopic TGFβ signaling results in ectopic mesenchymal transformation of the endocardium and thereby in improperly constituted distal OFT cushions. Our analysis highlights the interactions between myocardium, endocardium, and neural crest cells in outflow tract morphogenesis, and demonstrates the requirement for proper TGFβ signaling in outflow tract cushion organization and septation. Copyright © 2015. Published by Elsevier Inc.

Age differences in learning emerge from an insufficient representation of uncertainty in older adults

PubMed Central

Nassar, Matthew R.; Bruckner, Rasmus; Gold, Joshua I.; Li, Shu-Chen; Heekeren, Hauke R.; Eppinger, Ben

2016-01-01

Healthy aging can lead to impairments in learning that affect many laboratory and real-life tasks. These tasks often involve the acquisition of dynamic contingencies, which requires adjusting the rate of learning to environmental statistics. For example, learning rate should increase when expectations are uncertain (uncertainty), outcomes are surprising (surprise) or contingencies are more likely to change (hazard rate). In this study, we combine computational modelling with an age-comparative behavioural study to test whether age-related learning deficits emerge from a failure to optimize learning according to the three factors mentioned above. Our results suggest that learning deficits observed in healthy older adults are driven by a diminished capacity to represent and use uncertainty to guide learning. These findings provide insight into age-related cognitive changes and demonstrate how learning deficits can emerge from a failure to accurately assess how much should be learned. PMID:27282467

The potential for catastrophic dam failure at Lake Nyos maar, Cameroon

USGS Publications Warehouse

Lockwood, J.P.; Costa, J.E.; Tuttle, M.L.; Nni, J.; Tebor, S.G.

1988-01-01

The upper 40 m of Lake Nyos is bounded on the north by a narrow dam of poorly consolidated pyroclastic rocks, emplaced during the eruptive formation of the Lake Nyos maar a few hundred years ago. This 50-m-wide natural dam is structurally weak and is being eroded at an uncertain, but geologically alarming, rate. The eventual failure of the dam could cause a major flood (estimated peak discharge, 17000 m3/s) that would have a tragic impact on downstream areas as far as Nigeria, 108 km away. This serious hazard could be eliminated by lowering the lake level, either by controlled removal of the dam or by construction of a 680-m-long drainage tunnel about 65 m below the present lake surface. Either strategy would also lessen the lethal effects of future massive CO2 gas releases, such as the one that occurred in August 1986. ?? 1988 Springer-Verlag.

Study on Interference Suppression Algorithms for Electronic Noses: A Review

PubMed Central

Liang, Zhifang; Zhang, Ci; Sun, Hao; Liu, Tao

2018-01-01

Electronic noses (e-nose) are composed of an appropriate pattern recognition system and a gas sensor array with a certain degree of specificity and broad spectrum characteristics. The gas sensors have their own shortcomings of being highly sensitive to interferences which has an impact on the detection of target gases. When there are interferences, the performance of the e-nose will deteriorate. Therefore, it is urgent to study interference suppression techniques for e-noses. This paper summarizes the sources of interferences and reviews the advances made in recent years in interference suppression for e-noses. According to the factors which cause interference, interferences can be classified into two types: interference caused by changes of operating conditions and interference caused by hardware failures. The existing suppression methods were summarized and analyzed from these two aspects. Since the interferences of e-noses are uncertain and unstable, it can be found that some nonlinear methods have good effects for interference suppression, such as methods based on transfer learning, adaptive methods, etc. PMID:29649152

The true burden and risk of cholera: implications for prevention and control.

PubMed

Zuckerman, Jane N; Rombo, Lars; Fisch, Alain

2007-08-01

Cholera is a substantial health burden on the developing world and is endemic in Africa, Asia, South America, and Central America. The exact scale of the problem is uncertain because of limitations in existing surveillance systems, differences in reporting procedures, and failure to report cholera to WHO; official figures are likely to greatly underestimate the true prevalence of the disease. We have identified, through extensive literature searches, additional outbreaks of cholera to those reported to WHO, many of which originated from the Indian subcontinent and southeast Asia. Such underestimation of cholera can have important implications for decisions on provision of health interventions for indigenous populations, and on risk assessments for travellers. Furthermore, until recently, it has not been possible to implement public-health interventions in low-income countries to eliminate disease, and the prevention of cholera in travellers has been limited to restrictive guidelines. However, a vaccine against cholera is now available that has proven efficacy and tolerability in mass vaccination campaigns in low-income countries, and among travellers.

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2018-01-01

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Wind turbine model and loop shaping controller design

NASA Astrophysics Data System (ADS)

Gilev, Bogdan

2017-12-01

A model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. Model of the whole system is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model is developed a H∞ controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and H∞ controller.

Design Flexibility for Uncertain Distributed Generation from Photovoltaics

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

Palmintier, Bryan; Krishnamurthy, Dheepak; Wu, Hongyu

2016-12-12

Uncertainty in the future adoption patterns for distributed energy resources (DERs) introduces a challenge for electric distribution system planning. This paper explores the potential for flexibility in design - also known as real options - to identify design solutions that may never emerge when future DER patterns are treated as deterministic. A test case for storage system design with uncertain distributed generation for solar photovoltaics (DGPV) demonstrates this approach and is used to study sensitivities to a range of techno-economic assumptions.

Stronger steerability criterion for more uncertain continuous-variable systems

NASA Astrophysics Data System (ADS)

Chowdhury, Priyanka; Pramanik, Tanumoy; Majumdar, A. S.

2015-10-01

We derive a fine-grained uncertainty relation for the measurement of two incompatible observables on a single quantum system of continuous variables, and show that continuous-variable systems are more uncertain than discrete-variable systems. Using the derived fine-grained uncertainty relation, we formulate a stronger steering criterion that is able to reveal the steerability of NOON states that has hitherto not been possible using other criteria. We further obtain a monogamy relation for our steering inequality which leads to an, in principle, improved lower bound on the secret key rate of a one-sided device independent quantum key distribution protocol for continuous variables.

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.

PubMed

Benamor, Anouar; Messaoud, Hassani

2018-05-02

This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks. Published by Elsevier Ltd.

Application of implantable hemodynamic monitoring in the management of patients with diastolic heart failure: a subgroup analysis of the COMPASS-HF trial.

PubMed

Zile, Michael R; Bourge, Robert C; Bennett, Tom D; Stevenson, Lynne Warner; Cho, Yong K; Adamson, Philip B; Aaron, Mark F; Aranda, Juan M; Abraham, William T; Smart, Frank W; Kueffer, Fred J

2008-12-01

Nearly half of all patients with chronic heart failure (HF) have a normal ejection fraction (EF), and abnormal diastolic function (ie, diastolic heart failure [DHF]). However, appropriate management of DHF patients remains a difficult and uncertain challenge. The Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure (COMPASS-HF) trial was designed to evaluate whether an implantable hemodynamic monitor (IHM) was safe and effective in reducing the number of heart failure-related events (HFRE) in patients with chronic HF. The current study presents data on a prespecified and planned subgroup analysis from the COMPASS-HF trial: 70 patients with an EF > or =50% (ie, DHF). As such, this represents a subgroup analysis of the COMPASS-HF Trial. DHF patients were randomized to IHM-guided care (treatment) vs. standard care (control) for 6 months. All 70 patients received optimal medical therapy, but the hemodynamic information from the IHM was used to guide patient management only in the treatment group. The HFRE rate in DHF patients randomized to treatment was 0.58 events/6 months compared with DHF patients randomized to control, which was 0.73 events/6 months; this represented a 20% nonsignificant reduction in the overall HFRE rate in the treatment group (95% CI = -46, 56, P = .66). There was a 29% nonsignificant reduction in the relative risk of a HF hospitalization in the DHF patients randomized to treatment compared with DHF patients randomized to control (95% CI = -69, 70, P = .43). The IHM was shown to be safe and was associated with a very low system-related and procedure-related complication rate in DHF patients. However, in this subgroup analysis limited to 70 DHF patients, the addition IHM-guided care did not significantly lower the rate of HFR events. The results of this subgroup analysis in DHF patients, for whom there are currently no proven, effective management strategies, will be used to design future studies defining the effects of IHM-guided care in patients with DHF.

H∞ output tracking control of uncertain and disturbed nonlinear systems based on neural network model

NASA Astrophysics Data System (ADS)

Li, Chengcheng; Li, Yuefeng; Wang, Guanglin

2017-07-01

The work presented in this paper seeks to address the tracking problem for uncertain continuous nonlinear systems with external disturbances. The objective is to obtain a model that uses a reference-based output feedback tracking control law. The control scheme is based on neural networks and a linear difference inclusion (LDI) model, and a PDC structure and H∞ performance criterion are used to attenuate external disturbances. The stability of the whole closed-loop model is investigated using the well-known quadratic Lyapunov function. The key principles of the proposed approach are as follows: neural networks are first used to approximate nonlinearities, to enable a nonlinear system to then be represented as a linearised LDI model. An LMI (linear matrix inequality) formula is obtained for uncertain and disturbed linear systems. This formula enables a solution to be obtained through an interior point optimisation method for some nonlinear output tracking control problems. Finally, simulations and comparisons are provided on two practical examples to illustrate the validity and effectiveness of the proposed method.

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

PubMed

Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

2018-04-01

In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

Six sigma for revenue retrieval.

PubMed

Plonien, Cynthia

2013-01-01

Deficiencies in revenue retrieval due to failures in obtaining charges have contributed to a negative bottom line for numerous hospitals. Improving documentation practices through a Six Sigma process improvement initiative can minimize opportunities for errors through reviews and instill structure for compliance and consistency. Commitment to the Six Sigma principles with continuous monitoring of outcomes and constant communication of results to departments, management, and payers is a strong approach to reducing the financial impact of denials on an organization's revenues and expenses. Using Six Sigma tools can help improve the organization's financial performance not only for today, but also for health care's uncertain future.

Processing uncertain RFID data in traceability supply chains.

PubMed

Xie, Dong; Xiao, Jie; Guo, Guangjun; Jiang, Tong

2014-01-01

Radio Frequency Identification (RFID) is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries.

Processing Uncertain RFID Data in Traceability Supply Chains

PubMed Central

Xie, Dong; Xiao, Jie

2014-01-01

Radio Frequency Identification (RFID) is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries. PMID:24737978

Ga-67 positivity in sarcoidosis of the skin with coincident thyroid uptake of uncertain etiology

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

Moreno, A.J.; Brown, J.M.; Salinas, J.A.

1984-03-01

Gallium-67 citrate scintigraphy of a 26-year-old woman with systemic sarcoidosis demonstrated abnormal radiotracer uptake within multiple biopsy-proven sarcoidal cutaneous lesions and within both lobes of the thyroid gland. The etiology of the thyroidal uptake of the Ga-67 was uncertain but it may represent sarcoidal involvement of the gland.

Adaptive fixed-time control for cluster synchronisation of coupled complex networks with uncertain disturbances

NASA Astrophysics Data System (ADS)

Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming

2017-12-01

This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.

Application of dynamic uncertain causality graph in spacecraft fault diagnosis: Logic cycle

NASA Astrophysics Data System (ADS)

Yao, Quanying; Zhang, Qin; Liu, Peng; Yang, Ping; Zhu, Ma; Wang, Xiaochen

2017-04-01

Intelligent diagnosis system are applied to fault diagnosis in spacecraft. Dynamic Uncertain Causality Graph (DUCG) is a new probability graphic model with many advantages. In the knowledge expression of spacecraft fault diagnosis, feedback among variables is frequently encountered, which may cause directed cyclic graphs (DCGs). Probabilistic graphical models (PGMs) such as bayesian network (BN) have been widely applied in uncertain causality representation and probabilistic reasoning, but BN does not allow DCGs. In this paper, DUGG is applied to fault diagnosis in spacecraft: introducing the inference algorithm for the DUCG to deal with feedback. Now, DUCG has been tested in 16 typical faults with 100% diagnosis accuracy.

Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

PubMed

Zhang, Qichao; Zhao, Dongbin; Wang, Ding

2018-01-01

In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Takagi-Sugeno fuzzy model based robust dissipative control for uncertain flexible spacecraft with saturated time-delay input.

PubMed

Xu, Shidong; Sun, Guanghui; Sun, Weichao

2017-01-01

In this paper, the problem of robust dissipative control is investigated for uncertain flexible spacecraft based on Takagi-Sugeno (T-S) fuzzy model with saturated time-delay input. Different from most existing strategies, T-S fuzzy approximation approach is used to model the nonlinear dynamics of flexible spacecraft. Simultaneously, the physical constraints of system, like input delay, input saturation, and parameter uncertainties, are also taken care of in the fuzzy model. By employing Lyapunov-Krasovskii method and convex optimization technique, a novel robust controller is proposed to implement rest-to-rest attitude maneuver for flexible spacecraft, and the guaranteed dissipative performance enables the uncertain closed-loop system to reject the influence of elastic vibrations and external disturbances. Finally, an illustrative design example integrated with simulation results are provided to confirm the applicability and merits of the developed control strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Limitations imposed on fire PRA methods as the result of incomplete and uncertain fire event data.

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

Nowlen, Steven Patrick; Hyslop, J. S.

2010-04-01

Fire probabilistic risk assessment (PRA) methods utilize data and insights gained from actual fire events in a variety of ways. For example, fire occurrence frequencies, manual fire fighting effectiveness and timing, and the distribution of fire events by fire source and plant location are all based directly on the historical experience base. Other factors are either derived indirectly or supported qualitatively based on insights from the event data. These factors include the general nature and intensity of plant fires, insights into operator performance, and insights into fire growth and damage behaviors. This paper will discuss the potential methodology improvements thatmore » could be realized if more complete fire event reporting information were available. Areas that could benefit from more complete event reporting that will be discussed in the paper include fire event frequency analysis, analysis of fire detection and suppression system performance including incipient detection systems, analysis of manual fire fighting performance, treatment of fire growth from incipient stages to fully-involved fires, operator response to fire events, the impact of smoke on plant operations and equipment, and the impact of fire-induced cable failures on plant electrical circuits.« less

The development of biomarkers to reduce attrition rate in drug discovery focused on oncology and central nervous system.

PubMed

Safavi, Maliheh; Sabourian, Reyhaneh; Abdollahi, Mohammad

2016-10-01

The task of discovery and development of novel therapeutic agents remains an expensive, uncertain, time-consuming, competitive, and inefficient enterprise. Due to a steady increase in the cost and time of drug development and the considerable amount of resources required, a predictive tool is needed for assessing the safety and efficacy of a new chemical entity. This study is focused on the high attrition rate in discovery and development of oncology and central nervous system (CNS) medicines, because the failure rate of these medicines is higher than others. Some approaches valuable in reducing attrition rates are proposed and the judicious use of biomarkers is discussed. Unlike the significant progress made in identifying and characterizing novel mechanisms of disease processes and targeted therapies, the process of novel drug development is associated with an unacceptably high attrition rate. The application of clinically qualified predictive biomarkers holds great promise for further development of therapeutic targets, improved survival, and ultimately personalized medicine sets for patients. Decisions such as candidate selection, development risks, dose ranging, early proof of concept/principle, and patient stratification are based on the measurements of biologically and/or clinically validated biomarkers.

Identifying Model-Based Reconfiguration Goals through Functional Deficiencies

NASA Technical Reports Server (NTRS)

Benazera, Emmanuel; Trave-Massuyes, Louise

2004-01-01

Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Computer program for single input-output, single-loop feedback systems

NASA Technical Reports Server (NTRS)

1976-01-01

Additional work is reported on a completely automatic computer program for the design of single input/output, single loop feedback systems with parameter uncertainly, to satisfy time domain bounds on the system response to step commands and disturbances. The inputs to the program are basically the specified time-domain response bounds, the form of the constrained plant transfer function and the ranges of the uncertain parameters of the plant. The program output consists of the transfer functions of the two free compensation networks, in the form of the coefficients of the numerator and denominator polynomials, and the data on the prescribed bounds and the extremes actually obtained for the system response to commands and disturbances.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

Towards 50% wind electricity in Denmark: Dilemmas and challenges

NASA Astrophysics Data System (ADS)

Bach, Paul-Frederik

2016-05-01

Electricity and heat supply systems are essential contributors to a fossil-free future in Denmark. The combined production of heat and power (CHP) and the production of wind energy are already well developed in Denmark. Combined heat and power covers about 40% of the demand for space heating in Denmark, and the production of wind energy is supposed to exceed 50% of the demand for electricity by 2020. The changing electricity and heat production has some consequences already now: i) Decreasing wholesale prices in Denmark and in other countries. ii) Thermal power plants are closing down. Denmark is no longer self-sufficient with electricity under all conditions. iii) The electricity production pattern does not match the demand pattern. The result is that the neighbouring countries must absorb the variations from wind and solar power. Essential challenges: i) The future of combined heat and power in Denmark is uncertain. ii) Denmark will need new backup capacity for filling the gaps in wind power and solar cell output. iii) Flexible electricity consumers are supposed to contribute to balancing the future power systems. There is still a long way to go before the Smart Grid visions are implemented in large scale. iv) The transformation of the power system will create new risks of power failures.

Exercise training modalities in chronic heart failure: does high intensity aerobic interval training make the difference?

PubMed

Giallauria, Francesco; Smart, Neil Andrew; Cittadini, Antonio; Vigorito, Carlo

2016-10-14

Exercise training (ET) is strongly recommended in patients with chronic heart failure (CHF). Moderate-intensity aerobic continuous ET is the best established training modality in CHF patients. In the last decade, however, high-intensity interval exercise training (HIIT) has aroused considerable interest in cardiac rehabilitation community. Basically, HIIT consists of repeated bouts of high-intensity exercise alternated with recovery periods. In CHF patients, HIIT exerts larger improvements in exercise capacity compared to moderate-continuous ET. These results are intriguing, mostly considering that better functional capacity translates into an improvement of symptoms and quality of life. Notably, HIIT did not reveal major safety issues; although CHF patients should be clinically stable, have had recent exposure to at least regular moderate-intensity exercise, and appropriate supervision and monitoring during and after the exercise session are mandatory. The impact of HIIT on cardiac dimensions and function and on endothelial function remains uncertain. HIIT should not replace other training modalities in heart failure but should rather complement them. Combining and tailoring different ET modalities according to each patient's baseline clinical characteristics (i.e. exercise capacity, personal needs, preferences and goals) seem the most astute approach to exercise prescription.

Front air bag nondeployments in frontal crashes fatal to drivers or right-front passengers.

PubMed

Braver, Elisa R; McCartt, Anne T; Sherwood, Christopher P; Zuby, David S; Blanar, Laura; Scerbo, Marge

2010-04-01

Public concern has arisen about the reliability of front air bags because Fatality Analysis Reporting System (FARS) data indicate many nondeployed air bags in fatal frontal crashes. However, the accuracy of air bag deployment, the variable in question, is uncertain. This study aimed to provide more certain estimates of nondeployment incidence in fatal frontal crashes. Fatally injured passenger vehicle drivers and right-front passengers in frontal crashes were identified in two U.S. databases for calendar years 1998-2006 and model years 1994-2006: FARS, a census of police-reported fatal crashes on public roads, and National Automotive Sampling System/Crashworthiness Data System (NASS/CDS), a probability sample of tow-away crashes. NASS/CDS contains subsets of fatal crashes in FARS and collects detailed data using crash investigators. Front air bag deployment coding for front-seat occupant fatalities was compared in FARS and NASS/CDS, and case reviews were conducted. Among FARS frontal deaths with available deployment status (N = 43,169), front air bags were coded as not deployed for 18 percent of front occupants. In comparison, NASS/CDS (N = 628) reported 9 percent (weighted estimate) nondeployment among front occupants killed. Among crashes common to both databases, NASS/CDS reported deployments for 45 percent of front occupant deaths for which FARS had coded nondeployments. Detailed case reviews of NASS/CDS crashes indicated highly accurate coding for deployment status. Based on this case review, 8 percent (weighted estimate) of front occupant deaths in frontal crashes appeared to involve air bag nondeployments; 1-2 percent of front occupant deaths represented potential system failures where deployments would have been expected. Air bag deployments appeared unwarranted in most nondeployments based on crash characteristics. FARS data overstate the magnitude of the problem of air bag deployment failures; steps should be taken to improve coding. There are inherent uncertainties in judgments about whether or not air bags would be expected to deploy in some crashes. Continued monitoring of air bag performance is warranted.

Transient Stability Assessment of Power Systems With Uncertain Renewable Generation: Preprint

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

Villegas Pico, Hugo Nestor; Aliprantis, Dionysios C.; Lin, Xiaojun

2017-08-09

The transient stability of a power system depends heavily on its operational state at the moment of a fault. In systems where the penetration of renewable generation is significant, the dispatch of the conventional fleet of synchronous generators is uncertain at the time of dynamic security analysis. Hence, the assessment of transient stability requires the solution of a system of nonlinear ordinary differential equations with unknown initial conditions and inputs. To this end, we set forth a computational framework that relies on Taylor polynomials, where variables are associated with the level of renewable generation. This paper describes the details ofmore » the method and illustrates its application on a nine-bus test system.« less

Design of sliding-mode observer for a class of uncertain neutral stochastic systems

NASA Astrophysics Data System (ADS)

Liu, Zhen; Zhao, Lin; Zhu, Quanmin; Gao, Cunchen

2017-05-01

The problem of robust ? control for a class of uncertain neutral stochastic systems (NSS) is investigated by utilising the sliding-mode observer (SMO) technique. This paper presents a novel observer and integral-type sliding-surface design, based on which a new sufficient condition guaranteeing the resultant sliding-mode dynamics (SMDs) to be mean-square exponentially stable with a prescribed level of ? performance is derived. Then, an adaptive reaching motion controller is synthesised to lead the system to the predesigned sliding surface in finite-time almost surely. Finally, two illustrative examples are exhibited to verify the validity and superiority of the developed scheme.

Adaptive neural network backstepping control for a class of uncertain fractional-order chaotic systems with unknown backlash-like hysteresis

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

Wu, Yimin; Lv, Hui, E-mail: lvhui207@gmail.com

In this paper, we consider the control problem of a class of uncertain fractional-order chaotic systems preceded by unknown backlash-like hysteresis nonlinearities based on backstepping control algorithm. We model the hysteresis by using a differential equation. Based on the fractional Lyapunov stability criterion and the backstepping algorithm procedures, an adaptive neural network controller is driven. No knowledge of the upper bound of the disturbance and system uncertainty is required in our controller, and the asymptotical convergence of the tracking error can be guaranteed. Finally, we give two simulation examples to confirm our theoretical results.

Global adaptive control for uncertain nonaffine nonlinear hysteretic systems.

PubMed

Liu, Yong-Hua; Huang, Liangpei; Xiao, Dongming; Guo, Yong

2015-09-01

In this paper, the global output tracking is investigated for a class of uncertain nonlinear hysteretic systems with nonaffine structures. By combining the solution properties of the hysteresis model with the novel backstepping approach, a robust adaptive control algorithm is developed without constructing a hysteresis inverse. The proposed control scheme is further modified to tackle the bounded disturbances by adaptively estimating their bounds. It is rigorously proven that the designed adaptive controllers can guarantee global stability of the closed-loop system. Two numerical examples are provided to show the effectiveness of the proposed control schemes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Disease management in the treatment of patients with chronic heart failure who have universal access to health care: a randomized controlled trial.

PubMed

Kalter-Leibovici, Ofra; Freimark, Dov; Freedman, Laurence S; Kaufman, Galit; Ziv, Arnona; Murad, Havi; Benderly, Michal; Silverman, Barbara G; Friedman, Nurit; Cukierman-Yaffe, Tali; Asher, Elad; Grupper, Avishay; Goldman, Dorit; Amitai, Miriam; Matetzky, Shlomi; Shani, Mordechai; Silber, Haim

2017-05-01

The efficacy of disease management programs in improving the outcome of heart failure patients remains uncertain and may vary across health systems. This study explores whether a countrywide disease management program is superior to usual care in reducing adverse health outcomes and improving well-being among community-dwelling adult patients with moderate-to-severe chronic heart failure who have universal access to advanced health-care services and technologies. In this multicenter open-label trial, 1,360 patients recruited after hospitalization for heart failure exacerbation (38%) or from the community (62%) were randomly assigned to either disease management or usual care. Disease management, delivered by multi-disciplinary teams, included coordination of care, patient education, monitoring disease symptoms and patient adherence to medication regimen, titration of drug therapy, and home tele-monitoring of body weight, blood pressure and heart rate. Patients assigned to usual care were treated by primary care practitioners and consultant cardiologists. The primary composite endpoint was the time elapsed till first hospital admission for heart failure exacerbation or death from any cause. Secondary endpoints included the number of all hospital admissions, health-related quality of life and depression during follow-up. Intention-to-treat comparisons between treatments were adjusted for baseline patient data and study center. During the follow-up, 388 (56.9%) patients assigned to disease management and 387 (57.1%) assigned to usual care had a primary endpoint event. The median (range) time elapsed until the primary endpoint event or end of study was 2.0 (0-5.0) years among patients assigned to disease management, and 1.8 (0-5.0) years among patients assigned to usual care (adjusted hazard ratio, 0.908; 95% confidence interval, 0.788 to 1.047). Hospital admissions were mostly (70%) unrelated to heart failure. Patients assigned to disease management had a better health-related quality of life and a lower depression score during follow-up. This comprehensive disease management intervention was not superior to usual care with respect to the primary composite endpoint, but it improved health-related quality of life and depression. A disease-centered approach may not suffice to make a significant impact on hospital admissions and mortality in patients with chronic heart failure who have universal access to health care. Clinicaltrials.gov identifier: NCT00533013 . Trial registration date: 9 August 2007. Initial protocol release date: 20 September 2007.

Integrating planning and reactive control

NASA Technical Reports Server (NTRS)

Wilkins, David E.; Myers, Karen L.

1994-01-01

Our research is developing persistent agents that can achieve complex tasks in dynamic and uncertain environments. We refer to such agents as taskable, reactive agents. An agent of this type requires a number of capabilities. The ability to execute complex tasks necessitates the use of strategic plans for accomplishing tasks; hence, the agent must be able to synthesize new plans at run time. The dynamic nature of the environment requires that the agent be able to deal with unpredictable changes in its world. As such, agents must be able to react to unanticipated events by taking appropriate actions in a timely manner, while continuing activities that support current goals. The unpredictability of the world could lead to failure of plans generated for individual tasks. Agents must have the ability to recover from failures by adapting their activities to the new situation, or replanning if the world changes sufficiently. Finally, the agent should be able to perform in the face of uncertainty. The Cypress system, described here, provides a framework for creating taskable, reactive agents. Several features distinguish our approach: (1) the generation and execution of complex plans with parallel actions; (2) the integration of goal-driven and event driven activities during execution; (3) the use of evidential reasoning for dealing with uncertainty; and (4) the use of replanning to handle run-time execution problems. Our model for a taskable, reactive agent has two main intelligent components, an executor and a planner. The two components share a library of possible actions that the system can take. The library encompasses a full range of action representations, including plans, planning operators, and executable procedures such as predefined standard operating procedures (SOP's). These three classes of actions span multiple levels of abstraction.

Integrating planning and reactive control

NASA Astrophysics Data System (ADS)

Wilkins, David E.; Myers, Karen L.

1994-10-01

Our research is developing persistent agents that can achieve complex tasks in dynamic and uncertain environments. We refer to such agents as taskable, reactive agents. An agent of this type requires a number of capabilities. The ability to execute complex tasks necessitates the use of strategic plans for accomplishing tasks; hence, the agent must be able to synthesize new plans at run time. The dynamic nature of the environment requires that the agent be able to deal with unpredictable changes in its world. As such, agents must be able to react to unanticipated events by taking appropriate actions in a timely manner, while continuing activities that support current goals. The unpredictability of the world could lead to failure of plans generated for individual tasks. Agents must have the ability to recover from failures by adapting their activities to the new situation, or replanning if the world changes sufficiently. Finally, the agent should be able to perform in the face of uncertainty. The Cypress system, described here, provides a framework for creating taskable, reactive agents. Several features distinguish our approach: (1) the generation and execution of complex plans with parallel actions; (2) the integration of goal-driven and event driven activities during execution; (3) the use of evidential reasoning for dealing with uncertainty; and (4) the use of replanning to handle run-time execution problems. Our model for a taskable, reactive agent has two main intelligent components, an executor and a planner. The two components share a library of possible actions that the system can take. The library encompasses a full range of action representations, including plans, planning operators, and executable procedures such as predefined standard operating procedures (SOP's). These three classes of actions span multiple levels of abstraction.

Estimation in Linear Systems Featuring Correlated Uncertain Observations Coming from Multiple Sensors

NASA Astrophysics Data System (ADS)

Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

2009-08-01

In this paper, the state least-squares linear estimation problem from correlated uncertain observations coming from multiple sensors is addressed. It is assumed that, at each sensor, the state is measured in the presence of additive white noise and that the uncertainty in the observations is characterized by a set of Bernoulli random variables which are only correlated at consecutive time instants. Assuming that the statistical properties of such variables are not necessarily the same for all the sensors, a recursive filtering algorithm is proposed, and the performance of the estimators is illustrated by a numerical simulation example wherein a signal is estimated from correlated uncertain observations coming from two sensors with different uncertainty characteristics.

Stability analysis of fuzzy parametric uncertain systems.

PubMed

Bhiwani, R J; Patre, B M

2011-10-01

In this paper, the determination of stability margin, gain and phase margin aspects of fuzzy parametric uncertain systems are dealt. The stability analysis of uncertain linear systems with coefficients described by fuzzy functions is studied. A complexity reduced technique for determining the stability margin for FPUS is proposed. The method suggested is dependent on the order of the characteristic polynomial. In order to find the stability margin of interval polynomials of order less than 5, it is not always necessary to determine and check all four Kharitonov's polynomials. It has been shown that, for determining stability margin of FPUS of order five, four, and three we require only 3, 2, and 1 Kharitonov's polynomials respectively. Only for sixth and higher order polynomials, a complete set of Kharitonov's polynomials are needed to determine the stability margin. Thus for lower order systems, the calculations are reduced to a large extent. This idea has been extended to determine the stability margin of fuzzy interval polynomials. It is also shown that the gain and phase margin of FPUS can be determined analytically without using graphical techniques. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Hydraulic fracture propagation modeling and data-based fracture identification

NASA Astrophysics Data System (ADS)

Zhou, Jing

Successful shale gas and tight oil production is enabled by the engineering innovation of horizontal drilling and hydraulic fracturing. Hydraulically induced fractures will most likely deviate from the bi-wing planar pattern and generate complex fracture networks due to mechanical interactions and reservoir heterogeneity, both of which render the conventional fracture simulators insufficient to characterize the fractured reservoir. Moreover, in reservoirs with ultra-low permeability, the natural fractures are widely distributed, which will result in hydraulic fractures branching and merging at the interface and consequently lead to the creation of more complex fracture networks. Thus, developing a reliable hydraulic fracturing simulator, including both mechanical interaction and fluid flow, is critical in maximizing hydrocarbon recovery and optimizing fracture/well design and completion strategy in multistage horizontal wells. A novel fully coupled reservoir flow and geomechanics model based on the dual-lattice system is developed to simulate multiple nonplanar fractures' propagation in both homogeneous and heterogeneous reservoirs with or without pre-existing natural fractures. Initiation, growth, and coalescence of the microcracks will lead to the generation of macroscopic fractures, which is explicitly mimicked by failure and removal of bonds between particles from the discrete element network. This physics-based modeling approach leads to realistic fracture patterns without using the empirical rock failure and fracture propagation criteria required in conventional continuum methods. Based on this model, a sensitivity study is performed to investigate the effects of perforation spacing, in-situ stress anisotropy, rock properties (Young's modulus, Poisson's ratio, and compressive strength), fluid properties, and natural fracture properties on hydraulic fracture propagation. In addition, since reservoirs are buried thousands of feet below the surface, the parameters used in the reservoir flow simulator have large uncertainty. Those biased and uncertain parameters will result in misleading oil and gas recovery predictions. The Ensemble Kalman Filter is used to estimate and update both the state variables (pressure and saturations) and uncertain reservoir parameters (permeability). In order to directly incorporate spatial information such as fracture location and formation heterogeneity into the algorithm, a new covariance matrix method is proposed. This new method has been applied to a simplified single-phase reservoir and a complex black oil reservoir with complex structures to prove its capability in calibrating the reservoir parameters.

Probability-based constrained MPC for structured uncertain systems with state and random input delays

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Li, Dewei; Xi, Yugeng

2013-07-01

This article is concerned with probability-based constrained model predictive control (MPC) for systems with both structured uncertainties and time delays, where a random input delay and multiple fixed state delays are included. The process of input delay is governed by a discrete-time finite-state Markov chain. By invoking an appropriate augmented state, the system is transformed into a standard structured uncertain time-delay Markov jump linear system (MJLS). For the resulting system, a multi-step feedback control law is utilised to minimise an upper bound on the expected value of performance objective. The proposed design has been proved to stabilise the closed-loop system in the mean square sense and to guarantee constraints on control inputs and system states. Finally, a numerical example is given to illustrate the proposed results.

Use of Aminocaproic Acid in Combination With Extracorporeal Membrane Oxygenation in a Case of Leptospirosis Pulmonary Hemorrhage Syndrome.

PubMed

Pardinas, Miguel; Mendirichaga, Rodrigo; Budhrani, Gaurav; Garg, Rajan; Rosario, Luis; Rico, Rene; Panos, Anthony; Baier, Horst; Krick, Stefanie

2017-01-01

A 32-year-old man presented with a 10-day history of fever, chills, nausea, vomiting, myalgia, nonproductive cough, and worsening dyspnea after freshwater swimming in the Caribbean 1 week prior to presentation. Shortly after arrival at the hospital, the patient developed severe respiratory distress with massive hemoptysis. Based on serologic workup, he was diagnosed with leptospirosis pulmonary hemorrhage syndrome leading to diffuse alveolar hemorrhage, severe hypoxemic respiratory failure, and multiorgan failure. He received appropriate antibiotic coverage along with hemodynamic support with norepinephrine and vasopressin, mechanical ventilation, and renal replacement therapy in an intensive care unit. Introduction of extracorporeal membrane oxygenation was initiated to provide lung-protective ventilation supporting the recovery of his pulmonary function. Aminocaproic acid was used to stop and prevent further alveolar hemorrhage. He fully recovered thereafter; however, it is uncertain whether it was the use of aminocaproic acid that led to the resolution of his disease.

Use of Aminocaproic Acid in Combination With Extracorporeal Membrane Oxygenation in a Case of Leptospirosis Pulmonary Hemorrhage Syndrome

PubMed Central

Pardinas, Miguel; Mendirichaga, Rodrigo; Budhrani, Gaurav; Garg, Rajan; Rosario, Luis; Rico, Rene; Panos, Anthony; Baier, Horst; Krick, Stefanie

2017-01-01

A 32-year-old man presented with a 10-day history of fever, chills, nausea, vomiting, myalgia, nonproductive cough, and worsening dyspnea after freshwater swimming in the Caribbean 1 week prior to presentation. Shortly after arrival at the hospital, the patient developed severe respiratory distress with massive hemoptysis. Based on serologic workup, he was diagnosed with leptospirosis pulmonary hemorrhage syndrome leading to diffuse alveolar hemorrhage, severe hypoxemic respiratory failure, and multiorgan failure. He received appropriate antibiotic coverage along with hemodynamic support with norepinephrine and vasopressin, mechanical ventilation, and renal replacement therapy in an intensive care unit. Introduction of extracorporeal membrane oxygenation was initiated to provide lung-protective ventilation supporting the recovery of his pulmonary function. Aminocaproic acid was used to stop and prevent further alveolar hemorrhage. He fully recovered thereafter; however, it is uncertain whether it was the use of aminocaproic acid that led to the resolution of his disease. PMID:28469503

Radiosensitivity of cancer-initiating cells and normal stem cells (or what the Heisenberg uncertainly principle has to do with biology).

PubMed

Woodward, Wendy Ann; Bristow, Robert Glen

2009-04-01

Mounting evidence suggests that parallels between normal stem cell biology and cancer biology may provide new targets for cancer therapy. Prospective identification and isolation of cancer-initiating cells from solid tumors has promoted the descriptive and functional identification of these cells allowing for characterization of their response to contemporary cancer therapies, including chemotherapy and radiation. In clinical radiation therapy, the failure to clinically eradicate all tumor cells (eg, a lack of response, partial response, or nonpermanent complete response by imaging) is considered a treatment failure. As such, biologists have explored the characteristics of the small population of clonogenic cancer cells that can survive and are capable of repopulating the tumor after subcurative therapy. Herein, we discuss the convergence of these clonogenic studies with contemporary radiosensitivity studies that use cell surface markers to identify cancer-initiating cells. Implications for and uncertainties regarding incorporation of these concepts into the practice of modern radiation oncology are discussed.

Heart Failure Clinical Trials in East and Southeast Asia: Understanding the Importance and Defining the Next Steps

PubMed Central

Mentz, Robert J.; Roessig, Lothar; Greenberg, Barry H.; Sato, Naoki; Shinagawa, Kaori; Yeo, Daniel; Kwok, Bernard W.K.; Reyes, Eugenio B.; Krum, Henry; Pieske, Burkert; Greene, Stephen J.; Ambrosy, Andrew P.; Kelly, Jacob P.; Zannad, Faiez; Pitt, Bertram; Lam, Carolyn S.P.

2016-01-01

Heart failure (HF) is a major and increasing global public health problem. In Asia, aging populations and recent increases in cardiovascular risk factors have contributed to a particularly high burden of HF with similarly poor outcomes compared to the rest of the world. Representation of Asians in landmark HF trials has been variable. In addition, HF patients from Asia demonstrate clinical differences from other geographic regions. Thus, the generalizability of some clinical trials results to the Asian population remains uncertain. In this manuscript, we review differences in the HF phenotype, management and outcomes in patients from East and Southeast Asia. We describe lessons learned in Asia from recent HF registries and clinical trial databases and outline strategies to improve the potential for success in future trials. This review is based on discussions between scientists, clinical trialists, industry representatives and regulatory representatives at the CardioVascular Clinical Trialist Asia Forum on July 4, 2014. PMID:27256745

A robust H∞-tracking design for uncertain Takagi-Sugeno fuzzy systems with unknown premise variables using descriptor redundancy approach

NASA Astrophysics Data System (ADS)

Hassan Asemani, Mohammad; Johari Majd, Vahid

2015-12-01

This paper addresses a robust H∞ fuzzy observer-based tracking design problem for uncertain Takagi-Sugeno fuzzy systems with external disturbances. To have a practical observer-based controller, the premise variables of the system are assumed to be not measurable in general, which leads to a more complex design process. The tracker is synthesised based on a fuzzy Lyapunov function approach and non-parallel distributed compensation (non-PDC) scheme. Using the descriptor redundancy approach, the robust stability conditions are derived in the form of strict linear matrix inequalities (LMIs) even in the presence of uncertainties in the system, input, and output matrices simultaneously. Numerical simulations are provided to show the effectiveness of the proposed method.

Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

PubMed

Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

2014-07-01

This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Robust Control of Uncertain Systems via Dissipative LQG-Type Controllers

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2000-01-01

Optimal controller design is addressed for a class of linear, time-invariant systems which are dissipative with respect to a quadratic power function. The system matrices are assumed to be affine functions of uncertain parameters confined to a convex polytopic region in the parameter space. For such systems, a method is developed for designing a controller which is dissipative with respect to a given power function, and is simultaneously optimal in the linear-quadratic-Gaussian (LQG) sense. The resulting controller provides robust stability as well as optimal performance. Three important special cases, namely, passive, norm-bounded, and sector-bounded controllers, which are also LQG-optimal, are presented. The results give new methods for robust controller design in the presence of parametric uncertainties.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs

NASA Astrophysics Data System (ADS)

Wu, Bing-Fei; Ma, Li-Shan; Perng, Jau-Woei

This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.

Plan Debugging Using Approximate Domain Theories.

DTIC Science & Technology

1995-03-01

compelling suggestion that generative plan- ning systems solving large problems will need to exploit the control information implicit in uncertain...control information implicit in uncertain information may well lead the planner to expand one portion of a plan at one point, and a separate portion of...solutions that have been proposed are to abandon declarativism (as suggested in the work on situated automata theory and its variants [1, 16, 56, 72

Complacency and Automation Bias in the Use of Imperfect Automation.

PubMed

Wickens, Christopher D; Clegg, Benjamin A; Vieane, Alex Z; Sebok, Angelia L

2015-08-01

We examine the effects of two different kinds of decision-aiding automation errors on human-automation interaction (HAI), occurring at the first failure following repeated exposure to correctly functioning automation. The two errors are incorrect advice, triggering the automation bias, and missing advice, reflecting complacency. Contrasts between analogous automation errors in alerting systems, rather than decision aiding, have revealed that alerting false alarms are more problematic to HAI than alerting misses are. Prior research in decision aiding, although contrasting the two aiding errors (incorrect vs. missing), has confounded error expectancy. Participants performed an environmental process control simulation with and without decision aiding. For those with the aid, automation dependence was created through several trials of perfect aiding performance, and an unexpected automation error was then imposed in which automation was either gone (one group) or wrong (a second group). A control group received no automation support. The correct aid supported faster and more accurate diagnosis and lower workload. The aid failure degraded all three variables, but "automation wrong" had a much greater effect on accuracy, reflecting the automation bias, than did "automation gone," reflecting the impact of complacency. Some complacency was manifested for automation gone, by a longer latency and more modest reduction in accuracy. Automation wrong, creating the automation bias, appears to be a more problematic form of automation error than automation gone, reflecting complacency. Decision-aiding automation should indicate its lower degree of confidence in uncertain environments to avoid the automation bias. © 2015, Human Factors and Ergonomics Society.

Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system

NASA Astrophysics Data System (ADS)

Yang, Yana; Hua, Changchun; Li, Junpeng; Guan, Xinping

2017-12-01

This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler-Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.

Mergers and acquisitions: director and consultant liability exposure.

PubMed

Waxman, J M

1995-02-01

Corporate directors and their consultants must make decisions in an uncertain and changing health care environment. The losses each may face as a result of an incomplete analysis of the true value of the entities involved in mergers or acquisitions may extend beyond the failure of the transaction to the creation of personal liability as well. Accordingly, objective, careful, detailed, and fair decision-making based upon adequate information is more critical than ever for directors if they are to be able to take advantage of the business judgment rule, and also for consultants to avoid their own liability when transactions fail to deliver the values they have estimated.

Adler's psychology (of use) today: personal history of traumatic life events as a self-handicapping strategy.

PubMed

DeGree, C E; Snyder, C R

1985-06-01

We investigated the hypothesis that the reporting of a history of traumatic life events may serve as a strategy to control attributions about performance in an evaluative setting (i.e., self-handicapping). Following from Alfred Adler's early theorization in the psychology of use, as well as more recent theory and research on self-handicapping, we predicted that individuals would emphasize the adversity of events and experiences in their background when an uncertain evaluation was expected and when a traumatic background would serve as a suitable excuse for potential failure. Results generally supported the hypothesized self-protective reporting of traumatic life events.

Sensor trustworthiness in uncertain time varying stochastic environments

NASA Astrophysics Data System (ADS)

Verma, Ajay; Fernandes, Ronald; Vadakkeveedu, Kalyan

2011-06-01

Persistent surveillance applications require unattended sensors deployed in remote regions to track and monitor some physical stimulant of interest that can be modeled as output of time varying stochastic process. However, the accuracy or the trustworthiness of the information received through a remote and unattended sensor and sensor network cannot be readily assumed, since sensors may get disabled, corrupted, or even compromised, resulting in unreliable information. The aim of this paper is to develop information theory based metric to determine sensor trustworthiness from the sensor data in an uncertain and time varying stochastic environment. In this paper we show an information theory based determination of sensor data trustworthiness using an adaptive stochastic reference sensor model that tracks the sensor performance for the time varying physical feature, and provides a baseline model that is used to compare and analyze the observed sensor output. We present an approach in which relative entropy is used for reference model adaptation and determination of divergence of the sensor signal from the estimated reference baseline. We show that that KL-divergence is a useful metric that can be successfully used in determination of sensor failures or sensor malice of various types.

Stability of uncertain systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Blankenship, G. L.

1971-01-01

The asymptotic properties of feedback systems are discussed, containing uncertain parameters and subjected to stochastic perturbations. The approach is functional analytic in flavor and thereby avoids the use of Markov techniques and auxiliary Lyapunov functionals characteristic of the existing work in this area. The results are given for the probability distributions of the accessible signals in the system and are proved using the Prohorov theory of the convergence of measures. For general nonlinear systems, a result similar to the small loop-gain theorem of deterministic stability theory is given. Boundedness is a property of the induced distributions of the signals and not the usual notion of boundedness in norm. For the special class of feedback systems formed by the cascade of a white noise, a sector nonlinearity and convolution operator conditions are given to insure the total boundedness of the overall feedback system.

Dynamic Uncertain Causality Graph for Knowledge Representation and Reasoning: Utilization of Statistical Data and Domain Knowledge in Complex Cases.

PubMed

Zhang, Qin; Yao, Quanying

2018-05-01

The dynamic uncertain causality graph (DUCG) is a newly presented framework for uncertain causality representation and probabilistic reasoning. It has been successfully applied to online fault diagnoses of large, complex industrial systems, and decease diagnoses. This paper extends the DUCG to model more complex cases than what could be previously modeled, e.g., the case in which statistical data are in different groups with or without overlap, and some domain knowledge and actions (new variables with uncertain causalities) are introduced. In other words, this paper proposes to use -mode, -mode, and -mode of the DUCG to model such complex cases and then transform them into either the standard -mode or the standard -mode. In the former situation, if no directed cyclic graph is involved, the transformed result is simply a Bayesian network (BN), and existing inference methods for BNs can be applied. In the latter situation, an inference method based on the DUCG is proposed. Examples are provided to illustrate the methodology.

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

PubMed

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

NASA Astrophysics Data System (ADS)

Volyanskyy, Kostyantyn Y.

Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance rejection and noise suppression for nonnegative and compartmental dynamical systems with noise and exogenous system disturbances. We then use the developed framework to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of continuing hemorrhage and hemodilution. Critical care patients, whether undergoing surgery or recovering in intensive care units, require drug administration to regulate physiological variables such as blood pressure, cardiac output, heart rate, and degree of consciousness. The rate of infusion of each administered drug is critical, requiring constant monitoring and frequent adjustments. In this dissertation, we develop a neuroadaptive output feedback control framework for nonlinear uncertain nonnegative and compartmental systems with nonnegative control inputs and noisy measurements. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals. In addition, the neuroadaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space. Finally, the developed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of noisy electroencephalographic (EEG) measurements. Clinical trials demonstrate excellent regulation of unconsciousness allowing for a safe and effective administration of the anesthetic agent propofol. Furthermore, a neuroadaptive output feedback control architecture for nonlinear nonnegative dynamical systems with input amplitude and integral constraints is developed. Specifically, the neuroadaptive controller guarantees that the imposed amplitude and integral input constraints are satisfied and the physical system states remain in the nonnegative orthant of the state space. The proposed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for noncardiac surgery in the face of infusion rate constraints and a drug dosing constraint over a specified period. In addition, the aforementioned control architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework. Finally, a neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach

DTIC Science & Technology

2014-01-01

Paper DS-14-1028 to appear in the Special Issue on Stochastic Models, Control and Algorithms in Robotics, ASME Journal of Dynamic Systems...Measurement and Control Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach⋆ Devesh K. Jha† Yue Li† Thomas A. Wettergren‡† Asok...algorithm, called ν⋆, that was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control -theoretic

Building an evidence base for community health: a review of the quality of program evaluations.

PubMed

Jolley, Gwyn M; Lawless, Angela P; Baum, Fran E; Hurley, Catherine J; Fry, Denise

2007-11-01

An assessment of the quality of program evaluations conducted in South Australian community health services investigated how effective evaluation reporting is in producing an evidence base for community health. Evaluation reports were assessed by a team of reviewers. Practitioner workshops allowed an understanding of the uses of evaluation and what promotes or acts as a barrier to undertaking evaluations. Community health services do undertake a good deal of evaluation. However, reports were not generally explicit in dealing with the principles that underpin community health. Few engaged with program theory or rationale. Typically, reports were of short-term projects with uncertain futures so there may seem little point in considering issues of long-term health outcomes and transferability to other settings. The most important issue from our study is the lack of investment in applied health services research of the sort that will be required to produce the evidence for practice that policy makers desire. The current lack of evidence for community health reflects failure of the system to invest in research and evaluation that is adequately resourced and designed for complex community settings.

A framework for learning about improvement: embedded implementation and evaluation design to optimize learning

PubMed Central

Barry, Danika; Kimble, Leighann E; Nambiar, Bejoy; Parry, Gareth; Jha, Ashish; Chattu, Vijay Kumar; Massoud, M Rashad; Goldmann, Don

2018-01-01

Abstract Improving health care involves many actors, often working in complex adaptive systems. Interventions tend to be multi-factorial, implementation activities diverse, and contexts dynamic and complicated. This makes improvement initiatives challenging to describe and evaluate as matching evaluation and program designs can be difficult, requiring collaboration, trust and transparency. Collaboration is required to address important epidemiological principles of bias and confounding. If this does not take place, results may lack credibility because the association between interventions implemented and outcomes achieved is obscure and attribution uncertain. Moreover, lack of clarity about what was implemented, how it was implemented, and the context in which it was implemented often lead to disappointment or outright failure of spread and scale-up efforts. The input of skilled evaluators into the design and conduct of improvement initiatives can be helpful in mitigating these potential problems. While evaluation must be rigorous, if it is too rigid necessary adaptation and learning may be compromised. This article provides a framework and guidance on how improvers and evaluators can work together to design, implement and learn about improvement interventions more effectively. PMID:29873794

Robust Water Supply Infrastructure Development Pathways: What, When and Where Matters the Most? (INVITED)

NASA Astrophysics Data System (ADS)

Reed, Patrick; Zeff, Harrison; Characklis, Gregory

2017-04-01

Water supply adaptation frameworks that seek robustness must adaptively trigger actions that are contextually appropriate to emerging system observations and avoid long term high regret lock-ins. As an example, emerging water scarcity concerns in southeastern United States are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify regionally coordinated, scarcity-mitigating infrastructure development pathways that trigger time appropriate actions. Mistakes can lead to water shortages, overbuilt stranded assets and possibly financial failures. This presentation uses the Research Triangle area of North Carolina to illustrate the key concerns and challenges that emerged when helping Raleigh, Durham, Cary and Chapel Hill develop their long term water supply infrastructure pathways through 2060. This example shows how the region's water utilities' long term infrastructure pathways are strongly shaped by their short term conservation policies (i.e., reacting to evolving demands) and their ability to consider regional water transfers (i.e., reacting to supply imbalances). Cooperatively developed, shared investments across the four municipalities expand their capacity to use short term transfers to better manage severe droughts with fewer investments in irreversible infrastructure options. Cooperative pathways are also important for avoiding regional robustness conflicts, where one party benefits strongly at the expense of one or more the others. A significant innovation of this work is the exploitation of weekly and annual dynamic risk-of-failure action triggers that exploit evolving feedbacks between co-evolving human demands and regional supplies. These dynamic action triggers provide high levels of adaptivity, tailor actions to their specific context, and motivate the value of joint human—natural system observation systems. The insights from this work have general merit globally for urban regions where adjacent municipalities can benefit from cooperative planning.

Adaptive Jacobian Fuzzy Attitude Control for Flexible Spacecraft Combined Attitude and Sun Tracking System

NASA Astrophysics Data System (ADS)

Chak, Yew-Chung; Varatharajoo, Renuganth

2016-07-01

Many spacecraft attitude control systems today use reaction wheels to deliver precise torques to achieve three-axis attitude stabilization. However, irrecoverable mechanical failure of reaction wheels could potentially lead to mission interruption or total loss. The electrically-powered Solar Array Drive Assemblies (SADA) are usually installed in the pitch axis which rotate the solar arrays to track the Sun, can produce torques to compensate for the pitch-axis wheel failure. In addition, the attitude control of a flexible spacecraft poses a difficult problem. These difficulties include the strong nonlinear coupled dynamics between the rigid hub and flexible solar arrays, and the imprecisely known system parameters, such as inertia matrix, damping ratios, and flexible mode frequencies. In order to overcome these drawbacks, the adaptive Jacobian tracking fuzzy control is proposed for the combined attitude and sun-tracking control problem of a flexible spacecraft during attitude maneuvers in this work. For the adaptation of kinematic and dynamic uncertainties, the proposed scheme uses an adaptive sliding vector based on estimated attitude velocity via approximate Jacobian matrix. The unknown nonlinearities are approximated by deriving the fuzzy models with a set of linguistic If-Then rules using the idea of sector nonlinearity and local approximation in fuzzy partition spaces. The uncertain parameters of the estimated nonlinearities and the Jacobian matrix are being adjusted online by an adaptive law to realize feedback control. The attitude of the spacecraft can be directly controlled with the Jacobian feedback control when the attitude pointing trajectory is designed with respect to the spacecraft coordinate frame itself. A significant feature of this work is that the proposed adaptive Jacobian tracking scheme will result in not only the convergence of angular position and angular velocity tracking errors, but also the convergence of estimated angular velocity to the actual angular velocity. Numerical results are presented to demonstrate the effectiveness of the proposed scheme in tracking the desired attitude, as well as suppressing the elastic deflection effects of solar arrays during maneuver.

A new design of robust H∞ sliding mode control for uncertain stochastic T-S fuzzy time-delay systems.

PubMed

Gao, Qing; Feng, Gang; Xi, Zhiyu; Wang, Yong; Qiu, Jianbin

2014-09-01

In this paper, a novel dynamic sliding mode control scheme is proposed for a class of uncertain stochastic nonlinear time-delay systems represented by Takagi-Sugeno fuzzy models. The key advantage of the proposed scheme is that two very restrictive assumptions in most existing sliding mode control approaches for stochastic fuzzy systems have been removed. It is shown that the closed-loop control system trajectories can be driven onto the sliding surface in finite time almost certainly. It is also shown that the stochastic stability of the resulting sliding motion can be guaranteed in terms of linear matrix inequalities; moreover, the sliding-mode controller can be obtained simultaneously. Simulation results illustrating the advantages and effectiveness of the proposed approaches are also provided.

Robust decentralised stabilisation of uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative feedback

NASA Astrophysics Data System (ADS)

Li, Jian; Zhang, Qingling; Ren, Junchao; Zhang, Yanhao

2017-10-01

This paper studies the problem of robust stability and stabilisation for uncertain large-scale interconnected nonlinear descriptor systems via proportional plus derivative state feedback or proportional plus derivative output feedback. The basic idea of this work is to use the well-known differential mean value theorem to deal with the nonlinear model such that the considered nonlinear descriptor systems can be transformed into linear parameter varying systems. By using a parameter-dependent Lyapunov function, a decentralised proportional plus derivative state feedback controller and decentralised proportional plus derivative output feedback controller are designed, respectively such that the closed-loop system is quadratically normal and quadratically stable. Finally, a hypersonic vehicle practical simulation example and numerical example are given to illustrate the effectiveness of the results obtained in this paper.

Robust nonlinear variable selective control for networked systems

NASA Astrophysics Data System (ADS)

Rahmani, Behrooz

2016-10-01

This paper is concerned with the networked control of a class of uncertain nonlinear systems. In this way, Takagi-Sugeno (T-S) fuzzy modelling is used to extend the previously proposed variable selective control (VSC) methodology to nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set of fuzzy-blended locally linearised subsystems and further application of the VSC methodology to each subsystem. To increase the applicability of the T-S approach for uncertain nonlinear networked control systems, this study considers the asynchronous premise variables in the plant and the controller, and then introduces a robust stability analysis and control synthesis. The resulting optimal switching-fuzzy controller provides a minimum guaranteed cost on an H2 performance index. Simulation studies on three nonlinear benchmark problems demonstrate the effectiveness of the proposed method.

Continuous venovenous hemofiltration in the management of paraquat poisoning

PubMed Central

Lin, Guodong; Long, Jianhai; Luo, Yuan; Wang, Yongan; Zewu, Qiu

2017-01-01

Abstract Background: Paraquat (PQ) poisoning is a widespread occurrence, especially in underdeveloped areas. The treatment of PQ poisoning has always been difficult, and there is currently no definite effective treatment. Continuous venovenous hemofiltration (CVVH) treatment for PQ poisoning has been widely used in clinical practice; however, its effect remains uncertain. Accordingly, the purpose of this meta-analysis was to evaluate the efficacy of CVVH in the treatment of PQ poisoning. Methods: We searched for relevant trials using PubMed, Embase, the Cochrane Library, and 3 Chinese databases, the Chinese BioMedical Literature Database, National Knowledge Infrastructure Database, and Wanfang Database. We included all qualified randomized controlled trials (RCTs) of CVVH treatment for patients with PQ poisoning. The primary outcome was mortality, while the secondary outcomes included the survival time and constituent ratios of death due to respiratory failure and circulatory failure. Results: Three RCTs involving 290 patients were included. The mortality rates of the intervention and control groups were 57.9% and 61.0%, respectively. Pooled analysis demonstrated no significant difference in mortality between the CVVH treatment and control groups (risk ratio [RR] 0.94, 95% confidence interval [CI]: 0.78–1.15, P = .56), with a low level of heterogeneity (X2 = 1.75, I2 = 0%). However, the CVVH group was associated with a longer survival time compared to the control group (weighted mean difference 1.73, 95% CI: 0.56–2.90, P = .004). Respiratory failure as the cause of death was more common in the CVVH group, as compared with the control group (RR 1.66, 95% CI: 1.24–2.23, P = .0008), whereas patients in the control group were more likely to die from circulatory failure than in the CVVH group (RR 0.56, 95% CI: 0.40–0.81, P = .002). Conclusion: Although CVVH treatment might not noticeably reduce mortality for patients with PQ poisoning, it can prolong the survival time of the patients and improve the stability of the circulatory system, thereby enabling further treatment. PMID:28514303

Comparisons of Auditory Performance and Speech Intelligibility after Cochlear Implant Reimplantation in Mandarin-Speaking Users

PubMed Central

Hwang, Chung-Feng; Ko, Hui-Chen; Tsou, Yung-Ting; Chan, Kai-Chieh; Fang, Hsuan-Yeh; Wu, Che-Ming

2016-01-01

Objectives. We evaluated the causes, hearing, and speech performance before and after cochlear implant reimplantation in Mandarin-speaking users. Methods. In total, 589 patients who underwent cochlear implantation in our medical center between 1999 and 2014 were reviewed retrospectively. Data related to demographics, etiologies, implant-related information, complications, and hearing and speech performance were collected. Results. In total, 22 (3.74%) cases were found to have major complications. Infection (n = 12) and hard failure of the device (n = 8) were the most common major complications. Among them, 13 were reimplanted in our hospital. The mean scores of the Categorical Auditory Performance (CAP) and the Speech Intelligibility Rating (SIR) obtained before and after reimplantation were 5.5 versus 5.8 and 3.7 versus 4.3, respectively. The SIR score after reimplantation was significantly better than preoperation. Conclusions. Cochlear implantation is a safe procedure with low rates of postsurgical revisions and device failures. The Mandarin-speaking patients in this study who received reimplantation had restored auditory performance and speech intelligibility after surgery. Device soft failure was rare in our series, calling attention to Mandarin-speaking CI users requiring revision of their implants due to undesirable symptoms or decreasing performance of uncertain cause. PMID:27413753

New Approach For Prediction Groundwater Depletion

NASA Astrophysics Data System (ADS)

Moustafa, Mahmoud

2017-01-01

Current approaches to quantify groundwater depletion involve water balance and satellite gravity. However, the water balance technique includes uncertain estimation of parameters such as evapotranspiration and runoff. The satellite method consumes time and effort. The work reported in this paper proposes using failure theory in a novel way to predict groundwater saturated thickness depletion. An important issue in the failure theory proposed is to determine the failure point (depletion case). The proposed technique uses depth of water as the net result of recharge/discharge processes in the aquifer to calculate remaining saturated thickness resulting from the applied pumping rates in an area to evaluate the groundwater depletion. Two parameters, the Weibull function and Bayes analysis were used to model and analyze collected data from 1962 to 2009. The proposed methodology was tested in a nonrenewable aquifer, with no recharge. Consequently, the continuous decline in water depth has been the main criterion used to estimate the depletion. The value of the proposed approach is to predict the probable effect of the current applied pumping rates on the saturated thickness based on the remaining saturated thickness data. The limitation of the suggested approach is that it assumes the applied management practices are constant during the prediction period. The study predicted that after 300 years there would be an 80% probability of the saturated aquifer which would be expected to be depleted. Lifetime or failure theory can give a simple alternative way to predict the remaining saturated thickness depletion with no time-consuming processes such as the sophisticated software required.

Regional robust stabilisation and domain-of-attraction estimation for MIMO uncertain nonlinear systems with input saturation

NASA Astrophysics Data System (ADS)

Azizi, S.; Torres, L. A. B.; Palhares, R. M.

2018-01-01

The regional robust stabilisation by means of linear time-invariant state feedback control for a class of uncertain MIMO nonlinear systems with parametric uncertainties and control input saturation is investigated. The nonlinear systems are described in a differential algebraic representation and the regional stability is handled considering the largest ellipsoidal domain-of-attraction (DOA) inside a given polytopic region in the state space. A novel set of sufficient Linear Matrix Inequality (LMI) conditions with new auxiliary decision variables are developed aiming to design less conservative linear state feedback controllers with corresponding larger DOAs, by considering the polytopic description of the saturated inputs. A few examples are presented showing favourable comparisons with recently published similar control design methodologies.

Reducing regional drought vulnerabilities and multi-city robustness conflicts using many-objective optimization under deep uncertainty

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.; Herman, J. D.; Zeff, H. B.; Characklis, G. W.

2017-06-01

Emerging water scarcity concerns in many urban regions are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify coordinated, scarcity-mitigating strategies that trigger the appropriate actions needed to avoid water shortages and financial instabilities. This research focuses on the Research Triangle area of North Carolina, seeking to engage the water utilities within Raleigh, Durham, Cary and Chapel Hill in cooperative and robust regional water portfolio planning. Prior analysis of this region through the year 2025 has identified significant regional vulnerabilities to volumetric shortfalls and financial losses. Moreover, efforts to maximize the individual robustness of any of the mentioned utilities also have the potential to strongly degrade the robustness of the others. This research advances a multi-stakeholder Many-Objective Robust Decision Making (MORDM) framework to better account for deeply uncertain factors when identifying cooperative drought management strategies. Our results show that appropriately designing adaptive risk-of-failure action triggers required stressing them with a comprehensive sample of deeply uncertain factors in the computational search phase of MORDM. Search under the new ensemble of states-of-the-world is shown to fundamentally change perceived performance tradeoffs and substantially improve the robustness of individual utilities as well as the overall region to water scarcity. Search under deep uncertainty enhanced the discovery of how cooperative water transfers, financial risk mitigation tools, and coordinated regional demand management must be employed jointly to improve regional robustness and decrease robustness conflicts between the utilities. Insights from this work have general merit for regions where adjacent municipalities can benefit from cooperative regional water portfolio planning.

Glucagon-like peptide-1 receptor agonists and heart failure in type 2 diabetes: systematic review and meta-analysis of randomized and observational studies.

PubMed

Li, Ling; Li, Sheyu; Liu, Jiali; Deng, Ke; Busse, Jason W; Vandvik, Per Olav; Wong, Evelyn; Sohani, Zahra N; Bala, Malgorzata M; Rios, Lorena P; Malaga, German; Ebrahim, Shanil; Shen, Jiantong; Zhang, Longhao; Zhao, Pujing; Chen, Qunfei; Wang, Yingqiang; Guyatt, Gordon H; Sun, Xin

2016-05-11

The effect of glucagon-like peptide-1(GLP-1) receptor agonists on heart failure remains uncertain. We therefore conducted a systematic review to assess the possible impact of GLP-1 agonists on heart failure or hospitalization for heart failure in patients with type 2 diabetes. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov to identify randomized controlled trials (RCTs) and observational studies that addressed the effect of GLP-1 receptor agonists in adults with type 2 diabetes, and explicitly reported heart failure or hospitalization for heart failure. Two paired reviewers screened reports, collected data, and assessed the risk of bias. We pooled data from RCTs and observational studies separately, and used the GRADE approach to rate the quality of evidence. We identified 25 studies that were eligible for our review; 21 RCTs (n = 18,270) and 4 observational studies (n = 111,029). Low quality evidence from 20 RCTs suggested, if anything, a lower incidence of heart failure between GLP-1 agonists versus control (17/7,441 vs. 19/4,317; odds ratio (OR) 0.62, 95 % confidence interval (CI) 0.31 to 1.22; risk difference (RD) 19 fewer, 95 % CI 34 fewer to 11 more per 1000 over 5 years). Three cohort studies comparing GLP-1 agonists to alternative agents provided very low quality evidence that GLP-1 agonists do not increase the incidence of heart failure. One RCT provided moderate quality evidence that GLP-1 agonists were not associated with hospitalization for heart failure (lixisenatide vs placebo: 122/3,034 vs. 127/3,034; adjusted hazard ratio 0.96, 95 % CI 0.75 to 1.23; RD 4 fewer, 95 % CI 25 fewer to 23 more per 1000 over 5 years) and a case-control study provided very low quality evidence also suggesting no association (GLP-1 agonists vs. other anti-hyperglycemic drugs: 1118 cases and 17,626 controls, adjusted OR 0.67, 95 % CI 0.32 to 1.42). The current evidence suggests that GLP-1 agonists do not increase the risk of heart failure or hospitalization for heart failure among patients with type 2 diabetes.

Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply.

PubMed

Li, Kebai; Ma, Tianyi; Wei, Guo

2018-03-31

As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle and pole allocation method, and it is applied to an urban domestic water supply system with rising tendency and seasonal cycle fluctuation. To achieve this goal, first a multiplicative model is used to describe the urban domestic water demand. Then, a capital stock and a labor stock are selected as the state vector, and the investment and labor are designed as the control vector. Next, the compensator subsystem is devised in light of the internal model principle. Finally, by using the state feedback control strategy and pole allocation method, the multivariable robust economic control decision method is implemented. The implementation with this model can accomplish the urban domestic water supply control goal, with the robustness for the variation of parameters. The methodology presented in this study may be applied to the water management system in other parts of the world, provided all data used in this study are available. The robust control decision method in this paper is also applicable to deal with tracking control problems as well as stabilization control problems of other general dynamic uncertain systems.

Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply

PubMed Central

Li, Kebai; Ma, Tianyi; Wei, Guo

2018-01-01

As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle and pole allocation method, and it is applied to an urban domestic water supply system with rising tendency and seasonal cycle fluctuation. To achieve this goal, first a multiplicative model is used to describe the urban domestic water demand. Then, a capital stock and a labor stock are selected as the state vector, and the investment and labor are designed as the control vector. Next, the compensator subsystem is devised in light of the internal model principle. Finally, by using the state feedback control strategy and pole allocation method, the multivariable robust economic control decision method is implemented. The implementation with this model can accomplish the urban domestic water supply control goal, with the robustness for the variation of parameters. The methodology presented in this study may be applied to the water management system in other parts of the world, provided all data used in this study are available. The robust control decision method in this paper is also applicable to deal with tracking control problems as well as stabilization control problems of other general dynamic uncertain systems. PMID:29614749

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.

PubMed

Li, Pu; Chen, Bing

2011-04-01

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.

ACCF/ASE/AHA/ASNC/HFSA/HRS/SCAI/SCCM/SCCT/SCMR 2011 Appropriate Use Criteria for Echocardiography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography, American Heart Association, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance American College of Chest Physicians.

PubMed

Douglas, Pamela S; Garcia, Mario J; Haines, David E; Lai, Wyman W; Manning, Warren J; Patel, Ayan R; Picard, Michael H; Polk, Donna M; Ragosta, Michael; Parker Ward, R; Weiner, Rory B

2011-03-01

The American College of Cardiology Foundation (ACCF), in partnership with the American Society of Echocardiography (ASE) and along with key specialty and subspecialty societies, conducted a review of common clinical scenarios where echocardiography is frequently considered. This document combines and updates the original transthoracic and transesophageal echocardiography appropriateness criteria published in 2007 (1) and the original stress echocardiography appropriateness criteria published in 2008 (2). This revision reflects new clinical data, reflects changes in test utilization patterns,and clarifies echocardiography use where omissions or lack of clarity existed in the original criteria.The indications (clinical scenarios)were derived from common applications or anticipated uses, as well as from current clinical practice guidelines and results of studies examining the implementation of the original appropriate use criteria (AUC).The 202 indications in this document were developed by a diverse writing group and scored by a separate independent technical panel on a scale of 1 to 9,to designate appropriate use(median 7 to 9), uncertain use(median 4 to 6), and inappropriate use (median 1 to 3). Ninety-seven indications were rated as appropriate, 34 were rated as uncertain, and 71 were rated as inappropriate. In general,the use of echocardiography for initial diagnosis when there is a change in clinical status or when the results of the echocardiogram are anticipated to change patient management were rated appropriate. Routine testing when there was no change in clinical status or when results of testing were unlikely to modify management were more likely to be inappropriate than appropriate/uncertain.The AUC for echocardiography have the potential to impact physician decision making,healthcare delivery, and reimbursement policy. Furthermore,recognition of uncertain clinical scenarios facilitates identification of areas that would benefit from future research.

A coupled human-natural systems analysis of irrigated agriculture under changing climate

NASA Astrophysics Data System (ADS)

Giuliani, M.; Li, Y.; Castelletti, A.; Gandolfi, C.

2016-09-01

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.

State-space self-tuner for on-line adaptive control

NASA Technical Reports Server (NTRS)

Shieh, L. S.

1994-01-01

Dynamic systems, such as flight vehicles, satellites and space stations, operating in real environments, constantly face parameter and/or structural variations owing to nonlinear behavior of actuators, failure of sensors, changes in operating conditions, disturbances acting on the system, etc. In the past three decades, adaptive control has been shown to be effective in dealing with dynamic systems in the presence of parameter uncertainties, structural perturbations, random disturbances and environmental variations. Among the existing adaptive control methodologies, the state-space self-tuning control methods, initially proposed by us, are shown to be effective in designing advanced adaptive controllers for multivariable systems. In our approaches, we have embedded the standard Kalman state-estimation algorithm into an online parameter estimation algorithm. Thus, the advanced state-feedback controllers can be easily established for digital adaptive control of continuous-time stochastic multivariable systems. A state-space self-tuner for a general multivariable stochastic system has been developed and successfully applied to the space station for on-line adaptive control. Also, a technique for multistage design of an optimal momentum management controller for the space station has been developed and reported in. Moreover, we have successfully developed various digital redesign techniques which can convert a continuous-time controller to an equivalent digital controller. As a result, the expensive and unreliable continuous-time controller can be implemented using low-cost and high performance microprocessors. Recently, we have developed a new hybrid state-space self tuner using a new dual-rate sampling scheme for on-line adaptive control of continuous-time uncertain systems.

Parametric optimal control of uncertain systems under an optimistic value criterion

NASA Astrophysics Data System (ADS)

Li, Bo; Zhu, Yuanguo

2018-01-01

It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method.

Tsallis’ non-extensive free energy as a subjective value of an uncertain reward

NASA Astrophysics Data System (ADS)

Takahashi, Taiki

2009-03-01

Recent studies in neuroeconomics and econophysics revealed the importance of reward expectation in decision under uncertainty. Behavioral neuroeconomic studies have proposed that the unpredictability and the probability of an uncertain reward are distinctly encoded as entropy and a distorted probability weight, respectively, in the separate neural systems. However, previous behavioral economic and decision-theoretic models could not quantify reward-seeking and uncertainty aversion in a theoretically consistent manner. In this paper, we have: (i) proposed that generalized Helmholtz free energy in Tsallis’ non-extensive thermostatistics can be utilized to quantify a perceived value of an uncertain reward, and (ii) empirically examined the explanatory powers of the models. Future study directions in neuroeconomics and econophysics by utilizing the Tsallis’ free energy model are discussed.

Does stress perfusion imaging improve the diagnostic accuracy of late gadolinium enhanced cardiac magnetic resonance for establishing the etiology of heart failure?

PubMed

Gulsin, Gaurav S; Shetye, Abishek; Khoo, Jeffrey; Swarbrick, Daniel J; Levelt, Eylem; Lai, Florence Y; Squire, Iain B; Arnold, Jayanth R; McCann, Gerry P

2017-04-08

Late gadolinium enhanced cardiovascular magnetic resonance (LGE-CMR) has excellent specificity, sensitivity and diagnostic accuracy for differentiating between ischemic cardiomyopathy (ICM) and non-ischemic dilated cardiomyopathy (NICM). CMR first-pass myocardial perfusion imaging (perfusion-CMR) may also play role in distinguishing heart failure of ischemic and non-ischemic origins, although the utility of additional of stress perfusion imaging in such patients is unclear. The aim of this retrospective study was to assess whether the addition of adenosine stress perfusion imaging to LGE-CMR is of incremental value for differentiating ICM and NICM in patients with severe left ventricular systolic dysfunction (LVSD) of uncertain etiology. We retrospectively identified 100 consecutive adult patients (median age 69 years (IQR 59-73)) with severe LVSD (mean LV EF 26.6 ± 7.0%) referred for perfusion-CMR to establish the underlying etiology of heart failure. The cause of heart failure was first determined on examination of CMR cine and LGE images in isolation. Subsequent examination of complete adenosine stress perfusion-CMR studies (cine, LGE and perfusion images) was performed to identify whether this altered the initial diagnosis. On LGE-CMR, 38 patients were diagnosed with ICM, 46 with NICM and 16 with dual pathology. With perfusion-CMR, there were 39 ICM, 44 NICM and 17 dual pathology diagnoses. There was excellent agreement in diagnoses between LGE-CMR and perfusion-CMR (κ 0.968, p<0.001). The addition of adenosine stress perfusion images to LGE-CMR altered the diagnosis in only two of the 100 patients. The addition of adenosine stress perfusion-CMR to cine and LGE-CMR provides minimal incremental diagnostic yield for determining the etiology of heart failure in patients with severe LVSD.

Self-handicapping status, claimed self-handicaps and reduced practice effort following success and failure feedback.

PubMed

Thompson, T; Richardson, A

2001-03-01

Self-handicapping involves the strategic establishment of an impediment or obstacle to success prior to a performance situation which thereby provides a convenient excuse for poor performance. The study sought to establish that relative to low trait self-handicappers, high trait self-handicappers exposed to failure in an intellectually evaluative situation will (a) pre-emptively claim more handicaps, and (b) behaviourally self-handicap through reduced practice effort, and (c) report greater anxiety and negative affect relative to low trait self-handicappers. Participants were 72 undergraduate students, divided equally between high and low self-handicapping groups. This study utilised a 2 (self-handicapping status: high, low) x 3 (performance feedback: fail, low task importance; fail, high task importance; success) between-subjects factorial design to investigate claimed and behavioural self-handicapping through reduced practice effort. This was done by manipulating performance outcome and perceived task importance. Relative to low trait self-handicappers, high trait high self-handicappers claimed more handicaps and engaged in greater behavioural self-handicapping following failure when working on tasks that were described as potentially diagnostic of low ability. While low self-handicappers internalised their success more than their failure in the high task importance condition, high self-handicappers were undifferentiated in their attributions across performance conditions. Greater anxiety and greater negative affect were also characteristic of high self-handicappers. The study highlights the self-protective benefit of self-handicapping in sparing the individual from conclusions of low ability, and the failure of high self-handicappers to fully internalise their success. These elements and the role of uncertain estimates of ability are discussed in considering implications for intervention.

Perspectives on advance care planning among patients recently requiring non-invasive ventilation for acute respiratory failure: A qualitative study using thematic analysis.

PubMed

Smith, Tracy A; Disler, Rebecca T; Jenkins, Christine R; Ingham, Jane M; Davidson, Patricia M

2017-06-01

Patients requiring non-invasive ventilation for acute-on-chronic respiratory failure due to chronic obstructive pulmonary disease or heart failure exacerbations may have a poor prognosis underscoring the importance of advance care planning. We aimed to describe attitudes to, and experiences of, discussing the future among patients recently treated with non-invasive ventilation. Qualitative research using thematic analysis. Tertiary teaching hospital. Patients with acute hypercapnic respiratory failure requiring non-invasive ventilation. Individuals recently treated with non-invasive ventilation describe feeling the future is beyond their control and instead controlled by their illness. Participants often recognised their poor prognosis but avoided discussing some difficult topics. The majority preferred not to undergo cardiopulmonary resuscitation but most had not discussed this with healthcare professionals. When participants voiced concerns about their future health to family members, they were met with polarised responses. Some encountered willingness for further discussion, while others met deflection, deterring further conversation. An overarching narrative of 'Looking through my illness to an uncertain but concerning future' unites these themes. This study suggests opportunities and barriers for advance care planning in individuals with chronic disease. Patients' understanding of their prognosis and their attitudes to cardiopulmonary resuscitation suggests an opportunity for advance care planning. Structuring discussions around patients' preferences for care during future exacerbations may foster a sense of control over the future despite illness. The diversity of familial responses to patients' concerns about their future health has implications for advance care planning. These findings have the potential to improve care for patients with respiratory failure and suggest an important ongoing research agenda.

The predictive value of plasma biomarkers in discharged heart failure patients: role of plasma NT-proBNP.

PubMed

Leto, Laura; Testa, Marzia; Feola, Mauro

2016-04-01

Natriuretic peptides (NPs) have demonstrated their value to support clinical diagnosis of heart failure (HF); furthermore they are also studied for their prognostic role using them to guide appropriate management strategies. The present review gathers available evidence on prognostic role of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in patients hospitalized for acute decompensated heart failure (ADHF). We searched Medline for English-language studies with the sequent key-words: "acute heart failure/acute decompensated heart failure", "NT-proBNP/N-terminal pro-B type natriuretic peptide" and "prognosis/mortality/readmission". Almost 30 studies were included. NT-proBNP plasma levels at admission are strongly associated with all-cause short-term mortality (2-3 months), mid-term (6-11 months) or long- term mortality (more than one year) of follow-up. Regarding the prognostic power on cardiac death fewer data are available with uncertain results. NT-proBNP at discharge demonstrated its prognostic role for all-cause mortality at mid and long-term follow-up. The relation between NT-proBNP at discharge and cardiovascular mortality or composite end-point is under investigation. A decrease in NT-proBNP values during hospitalization provided prognostic prospects mainly for cardiovascular mortality and HF readmission. A 30% variation in NT-proBNP levels during in-hospital stay seemed to be an optimal cut-off for prognostic role. SNT-proBNP plasma levels proved to have a strong correlation with all-cause mortality, cardiovascular mortality, morbidity and composite outcomes in patients discharged after an ADHF. A better definition of the correct time of serial measurements and the cut-off values might be the challenge for the future investigations.

Prognostic Value of the Interaction between Galectin-3 and Antigen Carbohydrate 125 in Acute Heart Failure

PubMed Central

Núñez, Julio; Rabinovich, Gabriel A.; Sandino, Justo; Mainar, Luis; Palau, Patricia; Santas, Enrique; Villanueva, Maria Pilar; Núñez, Eduardo; Bodí, Vicent; Chorro, Francisco J.; Miñana, Gema; Sanchis, Juan

2015-01-01

Aims Galectin-3 (Gal-3) and carbohydrate antigen 125 (CA125) have emerged as robust prognostic biomarkers in heart failure. Experimental data have also suggested a potential molecular interaction between CA125 and Gal-3; however, the biological and clinical relevance of this interaction is still uncertain. We sought to evaluate, in patients admitted for acute heart failure, the association between plasma Gal-3 with all-cause mortality and the risk for rehospitalizations among high and low levels of CA125. Methods and Results We included 264 consecutive patients admitted for acute heart failure to the Cardiology Department in a third-level center. Both biomarkers were measured on admission. Negative binomial and Cox regression models were used to evaluate the prognostic effect of the interaction between Gal-3 and CA125 (dichotomized by its median) with hospital readmission and all-cause mortality, respectively. During a median follow-up of 2 years (IQR = 1-2.8), 108 (40.9%) patients deaths and 365 rehospitalizations in 171 (69.5%) patients were registered. In a multivariable setting, the effect of Gal-3 on mortality and rehospitalization was differentially mediated by CA125 (p = 0.007 and p<0.001, respectively). Indeed, in patients with CA125 above median (>67 U/ml), values across the continuum of Gal-3 showed a positive and almost linear relationship with either the risk of death or rehospitalization. Conversely, when CA125 was below median (≤67 U/ml), Gal-3 lacked any prognostic effect on both endpoints. Conclusion In patients with acute heart failure, Gal-3 was strongly associated with higher risk of long-term mortality and repeated rehospitalizations, but only in those patients exhibiting higher values of CA125 (above 67 U/ml). PMID:25875367

Living systematic review: 1. Introduction-the why, what, when, and how.

PubMed

Elliott, Julian H; Synnot, Anneliese; Turner, Tari; Simmonds, Mark; Akl, Elie A; McDonald, Steve; Salanti, Georgia; Meerpohl, Joerg; MacLehose, Harriet; Hilton, John; Tovey, David; Shemilt, Ian; Thomas, James

2017-11-01

Systematic reviews are difficult to keep up to date, but failure to do so leads to a decay in review currency, accuracy, and utility. We are developing a novel approach to systematic review updating termed "Living systematic review" (LSR): systematic reviews that are continually updated, incorporating relevant new evidence as it becomes available. LSRs may be particularly important in fields where research evidence is emerging rapidly, current evidence is uncertain, and new research may change policy or practice decisions. We hypothesize that a continual approach to updating will achieve greater currency and validity, and increase the benefits to end users, with feasible resource requirements over time. Copyright © 2017 Elsevier Inc. All rights reserved.

Cost-effectiveness of Out-of-Hospital Continuous Positive Airway Pressure for Acute Respiratory Failure.

PubMed

Thokala, Praveen; Goodacre, Steve; Ward, Matt; Penn-Ashman, Jerry; Perkins, Gavin D

2015-05-01

We determine the cost-effectiveness of out-of-hospital continuous positive airway pressure (CPAP) compared with standard care for adults presenting to emergency medical services with acute respiratory failure. We developed an economic model using a United Kingdom health care system perspective to compare the costs and health outcomes of out-of-hospital CPAP to standard care (inhospital noninvasive ventilation) when applied to a hypothetical cohort of patients with acute respiratory failure. The model assigned each patient a probability of intubation or death, depending on the patient's characteristics and whether he or she had out-of-hospital CPAP or standard care. The patients who survived accrued lifetime quality-adjusted life-years (QALYs) and health care costs according to their age and sex. Costs were accrued through intervention and hospital treatment costs, which depended on patient outcomes. All results were converted into US dollars, using the Organisation for Economic Co-operation and Development purchasing power parities rates. Out-of-hospital CPAP was more effective than standard care but was also more expensive, with an incremental cost-effectiveness ratio of £20,514 per QALY ($29,720/QALY) and a 49.5% probability of being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold. The probability of out-of-hospital CPAP's being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold depended on the incidence of eligible patients and varied from 35.4% when a low estimate of incidence was used to 93.8% with a high estimate. Variation in the incidence of eligible patients also had a marked influence on the expected value of sample information for a future randomized trial. The cost-effectiveness of out-of-hospital CPAP is uncertain. The incidence of patients eligible for out-of-hospital CPAP appears to be the key determinant of cost-effectiveness. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Cost-effectiveness of Out-of-Hospital Continuous Positive Airway Pressure for Acute Respiratory Failure

PubMed Central

Thokala, Praveen; Goodacre, Steve; Ward, Matt; Penn-Ashman, Jerry; Perkins, Gavin D.

2015-01-01

Study objective We determine the cost-effectiveness of out-of-hospital continuous positive airway pressure (CPAP) compared with standard care for adults presenting to emergency medical services with acute respiratory failure. Methods We developed an economic model using a United Kingdom health care system perspective to compare the costs and health outcomes of out-of-hospital CPAP to standard care (inhospital noninvasive ventilation) when applied to a hypothetical cohort of patients with acute respiratory failure. The model assigned each patient a probability of intubation or death, depending on the patient’s characteristics and whether he or she had out-of-hospital CPAP or standard care. The patients who survived accrued lifetime quality-adjusted life-years (QALYs) and health care costs according to their age and sex. Costs were accrued through intervention and hospital treatment costs, which depended on patient outcomes. All results were converted into US dollars, using the Organisation for Economic Co-operation and Development purchasing power parities rates. Results Out-of-hospital CPAP was more effective than standard care but was also more expensive, with an incremental cost-effectiveness ratio of £20,514 per QALY ($29,720/QALY) and a 49.5% probability of being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold. The probability of out-of-hospital CPAP’s being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold depended on the incidence of eligible patients and varied from 35.4% when a low estimate of incidence was used to 93.8% with a high estimate. Variation in the incidence of eligible patients also had a marked influence on the expected value of sample information for a future randomized trial. Conclusion The cost-effectiveness of out-of-hospital CPAP is uncertain. The incidence of patients eligible for out-of-hospital CPAP appears to be the key determinant of cost-effectiveness. PMID:25737210

Optimal second order sliding mode control for linear uncertain systems.

PubMed

Das, Madhulika; Mahanta, Chitralekha

2014-11-01

In this paper an optimal second order sliding mode controller (OSOSMC) is proposed to track a linear uncertain system. The optimal controller based on the linear quadratic regulator method is designed for the nominal system. An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances. To achieve finite time convergence of the sliding mode, a nonsingular terminal sliding surface is added with the integral sliding surface giving rise to a second order sliding mode controller. The main advantage of the proposed OSOSMC is that the control input is substantially reduced and it becomes chattering free. Simulation results confirm superiority of the proposed OSOSMC over some existing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive sensor-fault tolerant control for a class of multivariable uncertain nonlinear systems.

PubMed

Khebbache, Hicham; Tadjine, Mohamed; Labiod, Salim; Boulkroune, Abdesselem

2015-03-01

This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

PubMed

Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

2017-07-01

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

Climate change induced transformations of agricultural systems: insights from a global model

NASA Astrophysics Data System (ADS)

Leclère, D.; Havlík, P.; Fuss, S.; Schmid, E.; Mosnier, A.; Walsh, B.; Valin, H.; Herrero, M.; Khabarov, N.; Obersteiner, M.

2014-12-01

Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis.

Particle filter based hybrid prognostics for health monitoring of uncertain systems in bond graph framework

NASA Astrophysics Data System (ADS)

Jha, Mayank Shekhar; Dauphin-Tanguy, G.; Ould-Bouamama, B.

2016-06-01

The paper's main objective is to address the problem of health monitoring of system parameters in Bond Graph (BG) modeling framework, by exploiting its structural and causal properties. The system in feedback control loop is considered uncertain globally. Parametric uncertainty is modeled in interval form. The system parameter is undergoing degradation (prognostic candidate) and its degradation model is assumed to be known a priori. The detection of degradation commencement is done in a passive manner which involves interval valued robust adaptive thresholds over the nominal part of the uncertain BG-derived interval valued analytical redundancy relations (I-ARRs). The latter forms an efficient diagnostic module. The prognostics problem is cast as joint state-parameter estimation problem, a hybrid prognostic approach, wherein the fault model is constructed by considering the statistical degradation model of the system parameter (prognostic candidate). The observation equation is constructed from nominal part of the I-ARR. Using particle filter (PF) algorithms; the estimation of state of health (state of prognostic candidate) and associated hidden time-varying degradation progression parameters is achieved in probabilistic terms. A simplified variance adaptation scheme is proposed. Associated uncertainties which arise out of noisy measurements, parametric degradation process, environmental conditions etc. are effectively managed by PF. This allows the production of effective predictions of the remaining useful life of the prognostic candidate with suitable confidence bounds. The effectiveness of the novel methodology is demonstrated through simulations and experiments on a mechatronic system.

Rendezvous with connectivity preservation for multi-robot systems with an unknown leader

NASA Astrophysics Data System (ADS)

Dong, Yi

2018-02-01

This paper studies the leader-following rendezvous problem with connectivity preservation for multi-agent systems composed of uncertain multi-robot systems subject to external disturbances and an unknown leader, both of which are generated by a so-called exosystem with parametric uncertainty. By combining internal model design, potential function technique and adaptive control, two distributed control strategies are proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances. It is also worth to mention that the uncertain parameters in the multi-robot systems and exosystem are further allowed to belong to unknown and unbounded sets when applying the second fully distributed control law containing a dynamic gain inspired by high-gain adaptive control or self-tuning regulator.

Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems.

PubMed

Zhao, Xudong; Shi, Peng; Zheng, Xiaolong

2016-06-01

In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques.

The prehistory of haemodialysis as a treatment for uraemia.

PubMed

Cameron, J Stewart

2016-02-01

Less is generally known about the ideas, events and personalities which drove developments permitting the evolution of haemodialysis as a clinically useful form of palliation and treatment, than its subsequent success and failures. This pre-history of haemodialysis is summarized here. One must remember that with hindsight we can now discern connections between ideas and developments which were not perceptible in their time, and that progress towards any new idea, material or piece of hardware was usually random and undirected, and outcomes uncertain. We must also remember the many blind alleys we can now safely ignore, to give a spurious continuity to the development of ideas. The prehistory of dialysis begins with study of the diffusion of solute and solvent in osmosis in living systems and experimental settings, and the retention of potentially toxic substances in kidney failure, during the 18th and early 19th centuries. These two areas came together in work in the mid-19th century on diffusion of gases and liquids, and showed that natural and synthetic membranes could selectively hinder different solutes. This explained osmosis and allowed semi-permeable membranes to be used and designed. These ideas underpinned the subsequent history of both dialysis using body cavities such as the peritoneum (not discussed here) and ex vivo dialysis of blood. To perform this, new membranes and anticoagulants were needed. These led to the first attempts in animals in 1912-3, and human patients in 1924-8, but only the purification and synthesis of newer materials such as cellulose and heparin allowed practical and successful haemodialysis to evolve in the 1940s.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

Cooperatively surrounding control for multiple Euler-Lagrange systems subjected to uncertain dynamics and input constraints

NASA Astrophysics Data System (ADS)

Chen, Liang-Ming; Lv, Yue-Yong; Li, Chuan-Jiang; Ma, Guang-Fu

2016-12-01

In this paper, we investigate cooperatively surrounding control (CSC) of multi-agent systems modeled by Euler-Lagrange (EL) equations under a directed graph. With the consideration of the uncertain dynamics in an EL system, a backstepping CSC algorithm combined with neural-networks is proposed first such that the agents can move cooperatively to surround the stationary target. Then, a command filtered backstepping CSC algorithm is further proposed to deal with the constraints on control input and the absence of neighbors’ velocity information. Numerical examples of eight satellites surrounding one space target illustrate the effectiveness of the theoretical results. Project supported by the National Basic Research Program of China (Grant No. 2012CB720000) and the National Natural Science Foundation of China (Grant Nos. 61304005 and 61403103).

Robust passive control for a class of uncertain neutral systems based on sliding mode observer.

PubMed

Liu, Zhen; Zhao, Lin; Kao, Yonggui; Gao, Cunchen

2017-01-01

The passivity-based sliding mode control (SMC) problem for a class of uncertain neutral systems with unmeasured states is investigated. Firstly, a particular non-fragile state observer is designed to generate the estimations of the system states, based upon which a novel integral-type sliding surface function is established for the control process. Secondly, a new sufficient condition for robust asymptotic stability and passivity of the resultant sliding mode dynamics (SMDs) is obtained in terms of linear matrix inequalities (LMIs). Thirdly, the finite-time reachability of the predesigned sliding surface is ensured by resorting to a novel adaptive SMC law. Finally, the validity and superiority of the scheme are justified via several examples. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Terminal Sliding Mode-Based Consensus Tracking Control for Networked Uncertain Mechanical Systems on Digraphs.

PubMed

Chen, Gang; Song, Yongduan; Guan, Yanfeng

2018-03-01

This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.

Adaptive non-predictor control of lower triangular uncertain nonlinear systems with an unknown time-varying delay in the input

NASA Astrophysics Data System (ADS)

Koo, Min-Sung; Choi, Ho-Lim

2018-01-01

In this paper, we consider a control problem for a class of uncertain nonlinear systems in which there exists an unknown time-varying delay in the input and lower triangular nonlinearities. Usually, in the existing results, input delays have been coupled with feedforward (or upper triangular) nonlinearities; in other words, the combination of lower triangular nonlinearities and input delay has been rare. Motivated by the existing controller for input-delayed chain of integrators with nonlinearity, we show that the control of input-delayed nonlinear systems with two particular types of lower triangular nonlinearities can be done. As a control solution, we propose a newly designed feedback controller whose main features are its dynamic gain and non-predictor approach. Three examples are given for illustration.

An imprecise probability approach for squeal instability analysis based on evidence theory

NASA Astrophysics Data System (ADS)

Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

2017-01-01

An imprecise probability approach based on evidence theory is proposed for squeal instability analysis of uncertain disc brakes in this paper. First, the squeal instability of the finite element (FE) model of a disc brake is investigated and its dominant unstable eigenvalue is detected by running two typical numerical simulations, i.e., complex eigenvalue analysis (CEA) and transient dynamical analysis. Next, the uncertainty mainly caused by contact and friction is taken into account and some key parameters of the brake are described as uncertain parameters. All these uncertain parameters are usually involved with imprecise data such as incomplete information and conflict information. Finally, a squeal instability analysis model considering imprecise uncertainty is established by integrating evidence theory, Taylor expansion, subinterval analysis and surrogate model. In the proposed analysis model, the uncertain parameters with imprecise data are treated as evidence variables, and the belief measure and plausibility measure are employed to evaluate system squeal instability. The effectiveness of the proposed approach is demonstrated by numerical examples and some interesting observations and conclusions are summarized from the analyses and discussions. The proposed approach is generally limited to the squeal problems without too many investigated parameters. It can be considered as a potential method for squeal instability analysis, which will act as the first step to reduce squeal noise of uncertain brakes with imprecise information.

Robust master-slave synchronization for general uncertain delayed dynamical model based on adaptive control scheme.

PubMed

Wang, Tianbo; Zhou, Wuneng; Zhao, Shouwei; Yu, Weiqin

2014-03-01

In this paper, the robust exponential synchronization problem for a class of uncertain delayed master-slave dynamical system is investigated by using the adaptive control method. Different from some existing master-slave models, the considered master-slave system includes bounded unmodeled dynamics. In order to compensate the effect of unmodeled dynamics and effectively achieve synchronization, a novel adaptive controller with simple updated laws is proposed. Moreover, the results are given in terms of LMIs, which can be easily solved by LMI Toolbox in Matlab. A numerical example is given to illustrate the effectiveness of the method. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Feedforward/feedback control synthesis for performance and robustness

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang

1990-01-01

Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Elshall, A. S.

2014-12-01

Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

Introduced and invasive species in novel rangeland ecosystems: friends or foes?

USGS Publications Warehouse

Belnap, Jayne; Ludwig, John A.; Wilcox, Bradford P.; Betancourt, Julio L.; Dean, W. Richard J.; Hoffmann, Benjamin D.; Milton, Sue J.

2012-01-01

Globally, new combinations of introduced and native plant and animal species have changed rangelands into novel ecosystems. Whereas many rangeland stakeholders (people who use or have an interest in rangelands) view intentional species introductions to improve forage and control erosion as beneficial, others focus on unintended costs, such as increased fire risk, loss of rangeland biodiversity, and threats to conservation efforts, specifically in nature reserves and parks. These conflicting views challenge all rangeland stakeholders, especially those making decisions on how best to manage novel ecosystems. To formulate a conceptual framework for decision making, we examined a wide range of novel ecosystems, created by intentional and unintentional introductions of nonnative species and land-use–facilitated spread of native ones. This framework simply divides decision making into two types: 1) straightforward–certain, and 2) complex–uncertain. We argue that management decisions to retain novel ecosystems are certain when goods and services provided by the system far outweigh the costs of restoration, for example in the case of intensively managed Cenchrus pastures. Decisions to return novel ecosystems to natural systems are also certain when the value of the system is low and restoration is easy and inexpensive as in the case of biocontrol of Opuntia infestations. In contrast, decisions whether to retain or restore novel ecosystems become complex and uncertain in cases where benefits are low and costs of control are high as, for example, in the case of stopping the expansion of Prosopis and Juniperus into semiarid rangelands. Decisions to retain or restore novel ecosystems are also complex and uncertain when, for example, nonnative Eucalyptus trees expand along natural streams, negatively affecting biodiversity, but also providing timber and honey. When decision making is complex and uncertain, we suggest that rangeland managers utilize cost–benefit analyses and hold stakeholder workshops to resolve conflicts.

Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations.

PubMed

Karvetski, Christopher W; Lambert, James H; Linkov, Igor

2011-04-01

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation. Copyright © 2010 SETAC.

Global Warming and Ice Ages: I. Prospects For Physics Based Modulation of Global Change

DOE R&D Accomplishments Database

Teller, E.; Wood, L.; Hyde, R.

1996-08-15

It has been suggested that large-scale climate changes, mostly due to atmospheric injection of greenhouse gases connected with fossil-fired energy production, should be forestalled by internationally-agreed reductions in, e.g., electricity generation. The potential economic impacts of such limitations are obviously large: greater than or equal to $10{sup 11}/year. We propose that for far smaller - less than 1% - the mean thermal effects of greenhouse gases may be obviated in any of several distinct ways, some of them novel. These suggestions are all based on scatterers that prevent a small fraction of solar radiation from reaching all or part of the Earth. We propose research directed to quite near-term realization of one or more of these inexpensive approaches to cancel the effects of the greenhouse gas injection. While the magnitude of the climatic impact of greenhouse gases is currently uncertain, the prospect of severe failure of the climate, for instance at the onset of the next Ice Age, is undeniable. The proposals in this paper may lead to quite practical methods to reduce or eliminate all climate failures.

The economics (or lack thereof) of aerosol geoengineering

NASA Astrophysics Data System (ADS)

Goes, M.; Keller, K.; Tuana, N.

2009-04-01

Anthropogenic greenhouse gas emissions are changing the Earth's climate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid dangerous anthropogenic interference with the climate system. Recent proposals, however, call for the deployment of a different approach: to geoengineer climate by injecting aerosol precursors into the stratosphere. Published economic studies typically suggest that substituting aerosol geoengineering for abatement of carbon dioxide emissions results in large net monetary benefits. However, these studies neglect the risks of aerosol geoengineering due to (i) the potential for future geoengineering failures and (ii) the negative impacts associated with the aerosol forcing. Here we use a simple integrated assessment model of climate change to analyze potential economic impacts of aerosol geoengineering strategies over a wide range of uncertain parameters such as climate sensitivity, the economic damages due to climate change, and the economic damages due to aerosol geoengineering forcing. The simplicity of the model provides the advantages of parsimony and transparency, but it also imposes severe caveats on the interpretation of the results. For example, the analysis is based on a globally aggregated model and is hence silent on the question of intragenerational distribution of costs and benefits. In addition, the analysis neglects the effects of endogenous learning about the climate system. We show that the risks associated with a future geoengineering failure and negative impacts of aerosol forcings can cause geoenginering strategies to fail an economic cost-benefit test. One key to this finding is that a geoengineering failure would lead to dramatic and abrupt climatic changes. The monetary damages due to this failure can dominate the cost-benefit analysis because the monetary damages of climate change are expected to increase with the rate of change. Substituting aerosol geoengineering for greenhouse gas emission abatement might fail not only an economic cost-benefit test but also an ethical test of distributional justice. Substituting aerosol geoengineering for greenhouse gas emissions abatements constitutes a conscious risk transfer to future generations. Intergenerational justice demands distributional justice, namely that present generations may not create benefits for themselves in exchange for burdens on future generations. We use the economic model to quantify this risk transfer to better inform the judgment of whether substituting aerosol geoengineering for carbon dioxide emission abatement fails this ethical test.

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

NASA Astrophysics Data System (ADS)

Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig, Vicenc

2018-01-01

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.

National trends in rates of death and hospital admissions related to acute myocardial infarction, heart failure and stroke, 1994–2004

PubMed Central

Tu, Jack V.; Nardi, Lorelei; Fang, Jiming; Liu, Juan; Khalid, Laila; Johansen, Helen

2009-01-01

Background Rates of death from cardiovascular and cerebrovascular diseases have been steadily declining over the past few decades. Whether such declines are occurring to a similar degree for common disorders such as acute myocardial infarction, heart failure and stroke is uncertain. We examined recent national trends in mortality and rates of hospital admission for these 3 conditions. Methods We analyzed mortality data from Statistic Canada’s Canadian Mortality Database and data on hospital admissions from the Canadian Institute for Health Information’s Hospital Morbidity Database for the period 1994–2004. We determined age- and sex-standardized rates of death and hospital admissions per 100 000 population aged 20 years and over as well as in-hospital case-fatality rates. Results The overall age- and sex-standardized rate of death from cardiovascular disease in Canada declined 30.0%, from 360.6 per 100 000 in 1994 to 252.5 per 100 000 in 2004. During the same period, the rate fell 38.1% for acute myocardial infarction, 23.5% for heart failure and 28.2% for stroke, with improvements observed across most age and sex groups. The age- and sex-standardized rate of hospital admissions decreased 27.6% for stroke and 27.2% for heart failure. The rate for acute myocardial infarction fell only 9.2%. In contrast, the relative decline in the inhospital case-fatality rate was greatest for acute myocardial infarction (33.1%; p < 0.001). Much smaller relative improvements in case-fatality rates were noted for heart failure (8.1%) and stroke (8.9%). Interpretation The rates of death and hospital admissions for acute myocardial infarction, heart failure and stroke in Canada changed at different rates over the 10-year study period. Awareness of these trends may guide future efforts for health promotion and health care planning and help to determine priorities for research and treatment. PMID:19546444

Global sensitivity analysis in stochastic simulators of uncertain reaction networks.

PubMed

Navarro Jimenez, M; Le Maître, O P; Knio, O M

2016-12-28

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

Long-time uncertainty propagation using generalized polynomial chaos and flow map composition

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

Luchtenburg, Dirk M., E-mail: dluchten@cooper.edu; Brunton, Steven L.; Rowley, Clarence W.

2014-10-01

We present an efficient and accurate method for long-time uncertainty propagation in dynamical systems. Uncertain initial conditions and parameters are both addressed. The method approximates the intermediate short-time flow maps by spectral polynomial bases, as in the generalized polynomial chaos (gPC) method, and uses flow map composition to construct the long-time flow map. In contrast to the gPC method, this approach has spectral error convergence for both short and long integration times. The short-time flow map is characterized by small stretching and folding of the associated trajectories and hence can be well represented by a relatively low-degree basis. The compositionmore » of these low-degree polynomial bases then accurately describes the uncertainty behavior for long integration times. The key to the method is that the degree of the resulting polynomial approximation increases exponentially in the number of time intervals, while the number of polynomial coefficients either remains constant (for an autonomous system) or increases linearly in the number of time intervals (for a non-autonomous system). The findings are illustrated on several numerical examples including a nonlinear ordinary differential equation (ODE) with an uncertain initial condition, a linear ODE with an uncertain model parameter, and a two-dimensional, non-autonomous double gyre flow.« less

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

DOE PAGES

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-23

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes thatmore » the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.« less

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

NASA Astrophysics Data System (ADS)

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-01

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

NASA Technical Reports Server (NTRS)

Acikmese, Behcet A.; Carson, John M., III

2005-01-01

A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.

Continuous higher-order sliding mode control with time-varying gain for a class of uncertain nonlinear systems.

PubMed

Han, Yaozhen; Liu, Xiangjie

2016-05-01

This paper presents a continuous higher-order sliding mode (HOSM) control scheme with time-varying gain for a class of uncertain nonlinear systems. The proposed controller is derived from the concept of geometric homogeneity and super-twisting algorithm, and includes two parts, the first part of which achieves smooth finite time stabilization of pure integrator chains. The second part conquers the twice differentiable uncertainty and realizes system robustness by employing super-twisting algorithm. Particularly, time-varying switching control gain is constructed to reduce the switching control action magnitude to the minimum possible value while keeping the property of finite time convergence. Examples concerning the perturbed triple integrator chains and excitation control for single-machine infinite bus power system are simulated respectively to demonstrate the effectiveness and applicability of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Observer-based state tracking control of uncertain stochastic systems via repetitive controller

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Susana Ramya, L.; Selvaraj, P.

2017-08-01

This paper develops the repetitive control scheme for state tracking control of uncertain stochastic time-varying delay systems via equivalent-input-disturbance approach. The main purpose of this work is to design a repetitive controller to guarantee the tracking performance under the effects of unknown disturbances with bounded frequency and parameter variations. Specifically, a new set of linear matrix inequality (LMI)-based conditions is derived based on the suitable Lyapunov-Krasovskii functional theory for designing a repetitive controller which guarantees stability and desired tracking performance. More precisely, an equivalent-input-disturbance estimator is incorporated into the control design to reduce the effect of the external disturbances. Simulation results are provided to demonstrate the desired control system stability and their tracking performance. A practical stream water quality preserving system is also provided to show the effectiveness and advantage of the proposed approach.

Voluntary running exercise prevents β-cell failure in susceptible islets of the Zucker diabetic fatty rat.

PubMed

Delghingaro-Augusto, Viviane; Décary, Simon; Peyot, Marie-Line; Latour, Martin G; Lamontagne, Julien; Paradis-Isler, Nicolas; Lacharité-Lemieux, Marianne; Akakpo, Huguette; Birot, Olivier; Nolan, Christopher J; Prentki, Marc; Bergeron, Raynald

2012-01-15

Physical activity improves glycemic control in type 2 diabetes (T2D), but its contribution to preserving β-cell function is uncertain. We evaluated the role of physical activity on β-cell secretory function and glycerolipid/fatty acid (GL/FA) cycling in male Zucker diabetic fatty (ZDF) rats. Six-week-old ZDF rats engaged in voluntary running for 6 wk (ZDF-A). Inactive Zucker lean and ZDF (ZDF-I) rats served as controls. ZDF-I rats displayed progressive hyperglycemia with β-cell failure evidenced by falling insulinemia and reduced insulin secretion to oral glucose. Isolated ZDF-I rat islets showed reduced glucose-stimulated insulin secretion expressed per islet and per islet protein. They were also characterized by loss of the glucose regulation of fatty acid oxidation and GL/FA cycling, reduced mRNA expression of key β-cell genes, and severe reduction of insulin stores. Physical activity prevented diabetes in ZDF rats through sustaining β-cell compensation to insulin resistance shown in vivo and in vitro. Surprisingly, ZDF-A islets had persistent defects in fatty acid oxidation, GL/FA cycling, and β-cell gene expression. ZDF-A islets, however, had preserved islet insulin mRNA and insulin stores compared with ZDF-I rats. Physical activity did not prevent hyperphagia, dyslipidemia, or obesity in ZDF rats. In conclusion, islets of ZDF rats have a susceptibility to failure that is possibly due to altered β-cell fatty acid metabolism. Depletion of pancreatic islet insulin stores is a major contributor to islet failure in this T2D model, preventable by physical activity.

The economics and ethics of aerosol geoengineering strategies

NASA Astrophysics Data System (ADS)

Goes, Marlos; Keller, Klaus; Tuana, Nancy

2010-05-01

Anthropogenic greenhouse gas emissions are changing the Earth's climate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid dangerous anthropogenic interference with the climate system. Recent proposals, however, call for a different approach: geoengineering climate by injecting aerosol precursors into the stratosphere. Published economic studies typically neglect the risks of aerosol geoengineering due to (i) a potential failure to sustain the aerosol forcing and (ii) due to potential negative impacts associated with aerosol forcings. Here we use a simple integrated assessment model of climate change to analyze potential economic impacts of aerosol geoengineering strategies over a wide range of uncertain parameters such as climate sensitivity, the economic damages due to climate change, and the economic damages due to aerosol geoengineering forcings. The simplicity of the model provides the advantages of parsimony and transparency, but it also imposes considerable caveats. For example, the analysis is based on a globally aggregated model and is hence silent on intragenerational distribution of costs and benefits. In addition, the analysis neglects the effects of future learning and is based on a simple representation of climate change impacts. We use this integrated assessment model to show three main points. First, substituting aerosol geoengineering for the reduction of greenhouse gas emissions can fail the test of economic efficiency. One key to this finding is that a failure to sustain the aerosol forcing can lead to sizeable and abrupt climatic changes. The monetary damages due to such a discontinuous aerosol geoengineering can dominate the cost-benefit analysis because the monetary damages of climate change are expected to increase with the rate of change. Second, the relative contribution of aerosol geoengineering to an economically optimal portfolio hinges critically on deeply uncertain estimates of the damages due to aerosol forcing. Even if we assume that aerosol forcing could be deployed continuously, the aerosol geoengineering does not considerably displace the reduction of greenhouse gas emissions in the simple economic optimal growth model until the damages due to the aerosol forcing are rather low. Third, deploying aerosol geoengineering may also fail an ethical test regarding issues of intergenerational justice. Substituting aerosol geoengineering for reducing greenhouse gas emissions constitutes a conscious risk transfer to future generations, for example due to the increased risk of future abrupt climate change. This risk transfer is in tension with the requirement of intergenerational justice that present generations should not create benefits for themselves in exchange for burdens on future generations.

A robust adaptive observer for a class of singular nonlinear uncertain systems

NASA Astrophysics Data System (ADS)

Arefinia, Elaheh; Talebi, Heidar Ali; Doustmohammadi, Ali

2017-05-01

This paper proposes a robust adaptive observer for a class of singular nonlinear non-autonomous uncertain systems with unstructured unknown system and derivative matrices, and unknown bounded nonlinearities. Unlike many existing observers, no strong assumption such as Lipschitz condition is imposed on the recommended system. An augmented system is constructed, and the unknown bounds are calculated online using adaptive bounding technique. Considering the continuous nonlinear gain removes the chattering which may appear in practical applications such as analysis of electrical circuits and estimation of interaction force in beating heart robotic-assisted surgery. Moreover, a simple yet precise structure is attained which is easy to implement in many systems with significant uncertainties. The existence conditions of the standard form observer are obtained in terms of linear matrix inequality and the constrained generalised Sylvester's equations, and global stability is ensured. Finally, simulation results are obtained to evaluate the performance of the proposed estimator and demonstrate the effectiveness of the developed scheme.

The Effects of the Previous Outcome on Probabilistic Choice in Rats

PubMed Central

Marshall, Andrew T.; Kirkpatrick, Kimberly

2014-01-01

This study examined the effects of previous outcomes on subsequent choices in a probabilistic-choice task. Twenty-four rats were trained to choose between a certain outcome (1 or 3 pellets) versus an uncertain outcome (3 or 9 pellets), delivered with a probability of .1, .33, .67, and .9 in different phases. Uncertain outcome choices increased with the probability of uncertain food. Additionally, uncertain choices increased with the probability of uncertain food following both certain-choice outcomes and unrewarded uncertain choices. However, following uncertain-choice food outcomes, there was a tendency to choose the uncertain outcome in all cases, indicating that the rats continued to “gamble” after successful uncertain choices, regardless of the overall probability or magnitude of food. A subsequent manipulation, in which the probability of uncertain food varied within each session as a function of the previous uncertain outcome, examined how the previous outcome and probability of uncertain food affected choice in a dynamic environment. Uncertain-choice behavior increased with the probability of uncertain food. The rats exhibited increased sensitivity to probability changes and a greater degree of win–stay/lose–shift behavior than in the static phase. Simulations of two sequential choice models were performed to explore the possible mechanisms of reward value computations. The simulation results supported an exponentially decaying value function that updated as a function of trial (rather than time). These results emphasize the importance of analyzing global and local factors in choice behavior and suggest avenues for the future development of sequential-choice models. PMID:23205915

Real-time diagnostics of the reusable rocket engine using on-line system identification

NASA Technical Reports Server (NTRS)

Guo, T.-H.; Merrill, W.; Duyar, A.

1990-01-01

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Treatment of Acute Renal Failure Secondary to Multiple Myeloma with Chemotherapy and Extended High Cut-Off Hemodialysis

PubMed Central

Hutchison, Colin A.; Bradwell, Arthur R.; Cook, Mark; Basnayake, Kolitha; Basu, Supratik; Harding, Stephen; Hattersley, John; Evans, Neil D.; Chappel, Mike J.; Sampson, Paul; Foggensteiner, Lukas; Adu, Dwomoa; Cockwell, Paul

2009-01-01

Background and objectives: Extended hemodialysis using a high cut-off dialyzer (HCO-HD) removes large quantities of free light chains in patients with multiple myeloma. However, the clinical utility of this method is uncertain. This study assessed the combination of chemotherapy and HCO-HD on serum free light chain concentrations and renal recovery in patients with myeloma kidney (cast nephropathy) and dialysis-dependent acute renal failure. Design, setting, participants, & measurements: An open-label study of the relationship between free light chain levels and clinical outcomes in 19 patients treated with standard chemotherapy regimens and HCO-HD. Results: There were sustained early reductions in serum free light chain concentrations (median 85% [range 50 to 97]) in 13 patients. These 13 patients became dialysis independent at a median of 27 d (range 13 to 120). Six patients had chemotherapy interrupted because of early infections and did not achieve sustained early free light chain reductions; one of these patients recovered renal function (at 105 d) the remaining 5 patients did not recover renal function. Patients who recovered renal function had a significantly improved survival (P < 0.012). Conclusion: In dialysis-dependent acute renal failure secondary to myeloma kidney, patients who received uninterrupted chemotherapy and extended HCO-HD had sustained reductions in serum free light chain concentrations and recovered independent renal function. PMID:19339414

Uterine Deletion of Gp130 or Stat3 Shows Implantation Failure with Increased Estrogenic Responses

PubMed Central

Sun, Xiaofei; Bartos, Amanda; Whitsett, Jeffrey A.

2013-01-01

Leukemia inhibitory factor (LIF), a downstream target of estrogen, is essential for implantation in mice. LIF function is thought to be mediated by its binding to LIF receptor (LIFR) and recruitment of coreceptor GP130 (glycoprotein 130), and this receptor complex then activates signal transducer and activator of transcription (STAT)1/3. However, the importance of LIFR and GP130 acting via STAT3 in implantation remains uncertain, because constitutive inactivation of Lifr, Gp130, or Stat3 shows embryonic lethality in mice. To address this issue, we generated mice with conditional deletion of uterine Gp130 or Stat3 and show that both GP130 and STAT3 are critical for uterine receptivity and implantation. Implantation failure in these deleted mice is associated with higher uterine estrogenic responses prior to the time of implantation. These heightened estrogenic responses are not due to changes in ovarian hormone levels or expression of their nuclear receptors. In the deleted mice, estrogen-responsive gene, Lactoferrin (Ltf), and Mucin 1 protein, were up-regulated in the uterus. In addition, progesterone-responsive genes, Hoxa10 and Indian hedgehog (Ihh), were markedly down-regulated in STAT3-inactivated uteri. These changes in uteri of deleted mice were reflected by the failure of differentiation of the luminal epithelium, which is essential for blastocyst attachment. PMID:23885093

Rational temporal predictions can underlie apparent failures to delay gratification.

PubMed

McGuire, Joseph T; Kable, Joseph W

2013-04-01

An important category of seemingly maladaptive decisions involves failure to postpone gratification. A person pursuing a desirable long-run outcome may abandon it in favor of a short-run alternative that has been available all along. Here we present a theoretical framework in which this seemingly irrational behavior emerges from stable preferences and veridical judgments. Our account recognizes that decision makers generally face uncertainty regarding the time at which future outcomes will materialize. When timing is uncertain, the value of persistence depends crucially on the nature of a decision maker's prior temporal beliefs. Certain forms of temporal beliefs imply that a delay's predicted remaining length increases as a function of time already waited. In this type of situation, the rational, utility-maximizing strategy is to persist for a limited amount of time and then give up. We show empirically that people's explicit predictions of remaining delay lengths indeed increase as a function of elapsed time in several relevant domains, implying that temporal judgments offer a rational basis for limiting persistence. We then develop our framework into a simple working model and show how it accounts for individual differences in a laboratory task (the well-known "marshmallow test"). We conclude that delay-of-gratification failure, generally viewed as a manifestation of limited self-control capacity, can instead arise as an adaptive response to the perceived statistics of one's environment.

Rational temporal predictions can underlie apparent failures to delay gratification

PubMed Central

McGuire, Joseph T.; Kable, Joseph W.

2013-01-01

An important category of seemingly maladaptive decisions involves failure to postpone gratification. A person pursuing a desirable long-run outcome may abandon it in favor of a short-run alternative that has been available all along. Here we present a theoretical framework in which this seemingly irrational behavior emerges from stable preferences and veridical judgments. Our account recognizes that decision makers generally face uncertainty regarding the time at which future outcomes will materialize. When timing is uncertain, the value of persistence depends crucially on the nature of a decision-maker’s prior temporal beliefs. Certain forms of temporal beliefs imply that a delay’s predicted remaining length increases as a function of time already waited. In this type of situation, the rational, utility-maximizing strategy is to persist for a limited amount of time and then give up. We show empirically that people’s explicit predictions of remaining delay lengths indeed increase as a function of elapsed time in several relevant domains, implying that temporal judgments offer a rational basis for limiting persistence. We then develop our framework into a simple working model and show how it accounts for individual differences in a laboratory task (the well-known “marshmallow test”). We conclude that delay-of-gratification failure, generally viewed as a manifestation of limited self-control capacity, can instead arise as an adaptive response to the perceived statistics of one’s environment. PMID:23458085

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

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

Liu, Yunlong; Wang, Hong; Guo, Lei

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

An interval precise integration method for transient unbalance response analysis of rotor system with uncertainty

NASA Astrophysics Data System (ADS)

Fu, Chao; Ren, Xingmin; Yang, Yongfeng; Xia, Yebao; Deng, Wangqun

2018-07-01

A non-intrusive interval precise integration method (IPIM) is proposed in this paper to analyze the transient unbalance response of uncertain rotor systems. The transfer matrix method (TMM) is used to derive the deterministic equations of motion of a hollow-shaft overhung rotor. The uncertain transient dynamic problem is solved by combing the Chebyshev approximation theory with the modified precise integration method (PIM). Transient response bounds are calculated by interval arithmetic of the expansion coefficients. Theoretical error analysis of the proposed method is provided briefly, and its accuracy is further validated by comparing with the scanning method in simulations. Numerical results show that the IPIM can keep good accuracy in vibration prediction of the start-up transient process. Furthermore, the proposed method can also provide theoretical guidance to other transient dynamic mechanical systems with uncertainties.

Almost output regulation of LFT systems via gain-scheduling control

NASA Astrophysics Data System (ADS)

Yuan, Chengzhi; Duan, Chang; Wu, Fen

2018-05-01

Output regulation of general uncertain systems is a meaningful yet challenging problem. In spite of the rich literature in the field, the problem has not yet been addressed adequately due to the lack of an effective design mechanism. In this paper, we propose a new design framework for almost output regulation of uncertain systems described in the general form of linear fractional transformation (LFT) with time-varying parametric uncertainties and unknown external perturbations. A novel semi-LFT gain-scheduling output regulator structure is proposed, such that the associated control synthesis conditions guaranteeing both output regulation and ? disturbance attenuation performance are formulated as a set of linear matrix inequalities (LMIs) plus parameter-dependent linear matrix equations, which can be solved separately. A numerical example has been used to demonstrate the effectiveness of the proposed approach.

Finite-time output feedback control of uncertain switched systems via sliding mode design

NASA Astrophysics Data System (ADS)

Zhao, Haijuan; Niu, Yugang; Song, Jun

2018-04-01

The problem of sliding mode control (SMC) is investigated for a class of uncertain switched systems subject to unmeasurable state and assigned finite (possible short) time constraint. A key issue is how to ensure the finite-time boundedness (FTB) of system state during reaching phase and sliding motion phase. To this end, a state observer is constructed to estimate the unmeasured states. And then, a state estimate-based SMC law is designed such that the state trajectories can be driven onto the specified integral sliding surface during the assigned finite time interval. By means of partitioning strategy, the corresponding FTB over reaching phase and sliding motion phase are guaranteed and the sufficient conditions are derived via average dwell time technique. Finally, an illustrative example is given to illustrate the proposed method.

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

DOE PAGES

Liu, Yunlong; Wang, Hong; Guo, Lei

2018-03-26

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

Risk and resilience in an uncertain world

DOE PAGES

Dale, Virginia H.; Jager, Henriette I.; Wolfe, Amy K.; ...

2018-02-01

We report that because the future is uncertain and to some extent unknowable, it is imperative that ecologists become involved in the discussion and planning of future infrastructure and protection from the effects of altered disturbance regimes. Research can test and demonstrate the benefits of protecting or proactively managing important features and places, and processes that enhance provisioning of ecosystem services such as flood control and fire mitigation. In conclusion, it is time to demonstrate how ecological science, when applied to human–environmental systems, can reduce risks and enhance resilience in a complex, changing world.

Risk and resilience in an uncertain world

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

Dale, Virginia H.; Jager, Henriette I.; Wolfe, Amy K.

We report that because the future is uncertain and to some extent unknowable, it is imperative that ecologists become involved in the discussion and planning of future infrastructure and protection from the effects of altered disturbance regimes. Research can test and demonstrate the benefits of protecting or proactively managing important features and places, and processes that enhance provisioning of ecosystem services such as flood control and fire mitigation. In conclusion, it is time to demonstrate how ecological science, when applied to human–environmental systems, can reduce risks and enhance resilience in a complex, changing world.

NASA Instep/mdmsc Jitter Suppression Experiment (JITTER)

NASA Technical Reports Server (NTRS)

White, Edward V.

1992-01-01

The objectives are the following: (1) to develop and demonstrate in-space performance of both passive and active damping systems for suppression of micro-amplitude vibration on an actual application structure and operate despite uncertain dynamics and uncertain disturbance characteristics; and (2) to correlate ground and in-space performance - the performance metric is vibration attenuation. The goals are to achieve vibration suppression equivalent to 5 percent passive damping in selected models and 15 percent active damping in selected modes. Various aspects of this experiment are presented in viewgraph form.

Intelligent rover decision-making in response to exogenous events

NASA Technical Reports Server (NTRS)

Chouinard, C.; Estlin, T.; Gaines, D.; Fisher, F.

2005-01-01

This paper presents an introduction to the CLEAR system which performs rover command generation and re-planning, the challenges faced maintaining domain specific information in an uncertain environment, and the successes demonstrated with several methods of system testing.

Common Cause Failures and Ultra Reliability

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2012-01-01

A common cause failure occurs when several failures have the same origin. Common cause failures are either common event failures, where the cause is a single external event, or common mode failures, where two systems fail in the same way for the same reason. Common mode failures can occur at different times because of a design defect or a repeated external event. Common event failures reduce the reliability of on-line redundant systems but not of systems using off-line spare parts. Common mode failures reduce the dependability of systems using off-line spare parts and on-line redundancy.

Intelligent failure-tolerant control

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1991-01-01

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods.

Application of control theory to dynamic systems simulation

NASA Technical Reports Server (NTRS)

Auslander, D. M.; Spear, R. C.; Young, G. E.

1982-01-01

The application of control theory is applied to dynamic systems simulation. Theory and methodology applicable to controlled ecological life support systems are considered. Spatial effects on system stability, design of control systems with uncertain parameters, and an interactive computing language (PARASOL-II) designed for dynamic system simulation, report quality graphics, data acquisition, and simple real time control are discussed.

A structured analysis of in vitro failure loads and failure modes of fiber, metal, and ceramic post-and-core systems.

PubMed

Fokkinga, Wietske A; Kreulen, Cees M; Vallittu, Pekka K; Creugers, Nico H J

2004-01-01

This study sought to aggregate literature data on in vitro failure loads and failure modes of prefabricated fiber-reinforced composite (FRC) post systems and to compare them to those of prefabricated metal, custom-cast, and ceramic post systems. The literature was searched using MEDLINE from 1984 to 2003 for dental articles in English. Keywords used were (post or core or buildup or dowel) and (teeth or tooth). Additional inclusion/exclusion steps were conducted, each step by two independent readers: (1) Abstracts describing post-and-core techniques to reconstruct endodontically treated teeth and their mechanical and physical characteristics were included (descriptive studies or reviews were excluded); (2) articles that included FRC post systems were selected; (3) in vitro studies, single-rooted human teeth, prefabricated FRC posts, and composite as the core material were the selection criteria; and (4) failure loads and modes were extracted from the selected papers, and failure modes were dichotomized (distinction was made between "favorable failures," defined as reparable failures, and "unfavorable failures,"defined as irreparable [root] fractures). The literature search revealed 1,984 abstracts. Included were 244, 42, and 12 articles in the first, second, and third selection steps, respectively. Custom-cast post systems showed higher failure loads than prefabricated FRC post systems, whereas ceramic showed lower failure loads. Significantly more favorable failures occurred with prefabricated FRC post systems than with prefabricated and custom-cast metal post systems. The variable "post system" had a significant effect on mean failure loads. FRC post systems more frequently showed favorable failure modes than did metal post systems.

Disruptive Technology: An Uncertain Future

DTIC Science & Technology

2005-05-21

Technology that overturns market -- Military - Technology that causes a fundamental change in force structure, basing, and capability balance * Disruptive Technologies may arise from systems or enabling technology.

Multiobjective optimization in structural design with uncertain parameters and stochastic processes

NASA Technical Reports Server (NTRS)

Rao, S. S.

1984-01-01

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

NegBio: a high-performance tool for negation and uncertainty detection in radiology reports.

PubMed

Peng, Yifan; Wang, Xiaosong; Lu, Le; Bagheri, Mohammadhadi; Summers, Ronald; Lu, Zhiyong

2018-01-01

Negative and uncertain medical findings are frequent in radiology reports, but discriminating them from positive findings remains challenging for information extraction. Here, we propose a new algorithm, NegBio, to detect negative and uncertain findings in radiology reports. Unlike previous rule-based methods, NegBio utilizes patterns on universal dependencies to identify the scope of triggers that are indicative of negation or uncertainty. We evaluated NegBio on four datasets, including two public benchmarking corpora of radiology reports, a new radiology corpus that we annotated for this work, and a public corpus of general clinical texts. Evaluation on these datasets demonstrates that NegBio is highly accurate for detecting negative and uncertain findings and compares favorably to a widely-used state-of-the-art system NegEx (an average of 9.5% improvement in precision and 5.1% in F1-score). https://github.com/ncbi-nlp/NegBio.

Stabilization of a Quadrotor With Uncertain Suspended Load Using Sliding Mode Control

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

Zhou, Xu; Liu, Rui; Zhang, Jiucai

2016-08-21

The stability and trajectory control of a quadrotor carrying a suspended load with a fixed known mass has been extensively studied in recent years. However, the load mass is not always known beforehand in practical applications. This mass uncertainty brings uncertain disturbances to the quadrotor system, causing existing controllers to have a worse performance or to be collapsed. To improve the quadrotor's stability in this situation, we investigate the impacts of the uncertain load mass on the quadrotor. By comparing the simulation results of two controllers -- the proportional-derivative (PD) controller and the sliding mode controller (SMC) driven by amore » sliding mode disturbance of observer (SMDO), the quadrotor's performance is verified to be worse as the uncertainty increases. The simulation results also show a controller with stronger robustness against disturbances is better for practical applications.« less

Anti-windup adaptive PID control design for a class of uncertain chaotic systems with input saturation.

PubMed

Tahoun, A H

2017-01-01

In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Financial arrangements for health systems in low-income countries: an overview of systematic reviews.

PubMed

Wiysonge, Charles S; Paulsen, Elizabeth; Lewin, Simon; Ciapponi, Agustín; Herrera, Cristian A; Opiyo, Newton; Pantoja, Tomas; Rada, Gabriel; Oxman, Andrew D

2017-09-11

One target of the Sustainable Development Goals is to achieve "universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all". A fundamental concern of governments in striving for this goal is how to finance such a health system. This concern is very relevant for low-income countries. To provide an overview of the evidence from up-to-date systematic reviews about the effects of financial arrangements for health systems in low-income countries. Secondary objectives include identifying needs and priorities for future evaluations and systematic reviews on financial arrangements, and informing refinements in the framework for financial arrangements presented in the overview. We searched Health Systems Evidence in November 2010 and PDQ-Evidence up to 17 December 2016 for systematic reviews. We did not apply any date, language, or publication status limitations in the searches. We included well-conducted systematic reviews of studies that assessed the effects of financial arrangements on patient outcomes (health and health behaviours), the quality or utilisation of healthcare services, resource use, healthcare provider outcomes (such as sick leave), or social outcomes (such as poverty, employment, or financial burden of patients, e.g. out-of-pocket payment, catastrophic disease expenditure) and that were published after April 2005. We excluded reviews with limitations important enough to compromise the reliability of the findings. Two overview authors independently screened reviews, extracted data, and assessed the certainty of evidence using GRADE. We prepared SUPPORT Summaries for eligible reviews, including key messages, 'Summary of findings' tables (using GRADE to assess the certainty of the evidence), and assessments of the relevance of findings to low-income countries. We identified 7272 reviews and included 15 in this overview, on: collection of funds (2 reviews), insurance schemes (1 review), purchasing of services (1 review), recipient incentives (6 reviews), and provider incentives (5 reviews). The reviews were published between 2008 and 2015; focused on 13 subcategories; and reported results from 276 studies: 115 (42%) randomised trials, 11 (4%) non-randomised trials, 23 (8%) controlled before-after studies, 51 (19%) interrupted time series, 9 (3%) repeated measures, and 67 (24%) other non-randomised studies. Forty-three per cent (119/276) of the studies included in the reviews took place in low- and middle-income countries. Collection of funds: the effects of changes in user fees on utilisation and equity are uncertain (very low-certainty evidence). It is also uncertain whether aid delivered under the Paris Principles (ownership, alignment, harmonisation, managing for results, and mutual accountability) improves health outcomes compared to aid delivered without conforming to those principles (very low-certainty evidence). Insurance schemes: community-based health insurance may increase service utilisation (low-certainty evidence), but the effects on health outcomes are uncertain (very low-certainty evidence). It is uncertain whether social health insurance improves utilisation of health services or health outcomes (very low-certainty evidence). Purchasing of services: it is uncertain whether increasing salaries of public sector healthcare workers improves the quantity or quality of their work (very low-certainty evidence). Recipient incentives: recipient incentives may improve adherence to long-term treatments (low-certainty evidence), but it is uncertain whether they improve patient outcomes. One-time recipient incentives probably improve patient return for start or continuation of treatment (moderate-certainty evidence) and may improve return for tuberculosis test readings (low-certainty evidence). However, incentives may not improve completion of tuberculosis prophylaxis, and it is uncertain whether they improve completion of treatment for active tuberculosis. Conditional cash transfer programmes probably lead to an increase in service utilisation (moderate-certainty evidence), but their effects on health outcomes are uncertain. Vouchers may improve health service utilisation (low-certainty evidence), but the effects on health outcomes are uncertain (very low-certainty evidence). Introducing a restrictive cap may decrease use of medicines for symptomatic conditions and overall use of medicines, may decrease insurers' expenditures on medicines (low-certainty evidence), and has uncertain effects on emergency department use, hospitalisations, and use of outpatient care (very low-certainty evidence). Reference pricing, maximum pricing, and index pricing for drugs have mixed effects on drug expenditures by patients and insurers as well as the use of brand and generic drugs. Provider incentives: the effects of provider incentives are uncertain (very low-certainty evidence), including: the effects of provider incentives on the quality of care provided by primary care physicians or outpatient referrals from primary to secondary care, incentives for recruiting and retaining health professionals to serve in remote areas, and the effects of pay-for-performance on provider performance, the utilisation of services, patient outcomes, or resource use in low-income countries. Research based on sound systematic review methods has evaluated numerous financial arrangements relevant to low-income countries, targeting different levels of the health systems and assessing diverse outcomes. However, included reviews rarely reported social outcomes, resource use, equity impacts, or undesirable effects. We also identified gaps in primary research because of uncertainty about applicability of the evidence to low-income countries. Financial arrangements for which the effects are uncertain include external funding (aid), caps and co-payments, pay-for-performance, and provider incentives. Further studies evaluating the effects of these arrangements are needed in low-income countries. Systematic reviews should include all outcomes that are relevant to decision-makers and to people affected by changes in financial arrangements.

Robust planning of sanitation services in urban informal settlements: An analytical framework.

PubMed

Schmitt, Rafael J P; Morgenroth, Eberhard; Larsen, Tove A

2017-03-01

New types of sanitation services are emerging to tackle the sanitation crisis in informal settlements. These services link toilet facilities to semi-decentralized treatment plants via frequent, road-based transport of excreta. However, information for the planning of such sanitation services is scarce, and their future operating conditions are highly uncertain. The key questions of this paper are therefore: a) what are the drivers behind success or failure of a service-based sanitation system in informal settlements and b) on what scales and under which conditions can such a system operate successfully? To answer these questions, already at an early stage of the planning process, we introduce a stochastic model to analyze a wide range of system designs under varying technical designs, socio-economic factors, and spatial condition. Based on these initial results, we design a sanitation service and use the numeric model to study its reliability and costs over a wide range of scales, i.e., system capacities, from very few to many hundred users per semi-decentralized treatment unit. Key findings are that such a system can only operate within a narrow, but realistic range of conditions. Key requirements are toilet facilities, which can be serviced rapidly, and a flexible workforce. A high density of facilities will also lower the costs. Under these premises, we develop a road-based sanitation service and model its functionality in different settings and under many scenarios. Results show that the developed sanitation system using a single vehicle is scalable (100-700 users), can provide reliable service, and can be cheap (<1.5 c/p/day). Hence, this paper demonstrates opportunities for road-based sanitation in informal settlements and presents a quantitative framework for designing such systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climate change adaptation in regulated water utilities

NASA Astrophysics Data System (ADS)

Vicuna, S.; Melo, O.; Harou, J. J.; Characklis, G. W.; Ricalde, I.

2017-12-01

Concern about climate change impacts on water supply systems has grown in recent years. However, there are still few examples of pro-active interventions (e.g. infrastructure investment or policy changes) meant to address plausible future changes. Deep uncertainty associated with climate impacts, future demands, and regulatory constraints might explain why utility planning in a range of contexts doesn't explicitly consider climate change scenarios and potential adaptive responses. Given the importance of water supplies for economic development and the cost and longevity of many water infrastructure investments, large urban water supply systems could suffer from lack of pro-active climate change adaptation. Water utilities need to balance the potential for high regret stranded assets on the one side, with insufficient supplies leading to potentially severe socio-economic, political and environmental failures on the other, and need to deal with a range of interests and constraints. This work presents initial findings from a project looking at how cities in Chile, the US and the UK are developing regulatory frameworks that incorporate utility planning under uncertainty. Considering for example the city of Santiago, Chile, recent studies have shown that although high scarcity cost scenarios are plausible, pre-emptive investment to guard from possible water supply failures is still remote and not accommodated by current planning practice. A first goal of the project is to compare and contrast regulatory approaches to utility risks considering climate change adaptation measures. Subsequently we plan to develop and propose a custom approach for the city of Santiago based on lessons learned from other contexts. The methodological approach combines institutional assessment of water supply regulatory frameworks with simulation-based decision-making under uncertainty approaches. Here we present initial work comparing the regulatory frameworks in Chile, UK and USA evaluating their ability to incorporate uncertain climate and other changes into long-term infrastructure investment planning. The potential for regulatory and financial adaptive measures is explored in addition to a discussion on evaluating their appropriateness via various modelling-based intervention decision-making approaches.

How do we approach thrombocytopenia in critically ill patients?

PubMed

Thachil, Jecko; Warkentin, Theodore E

2017-04-01

A low platelet count is a frequently encountered haematological abnormality in patients treated in intensive treatment units (ITUs). Although severe thrombocytopenia (platelet count <20 × 10 9 /l) can be associated with bleeding, even moderate-degree thrombocytopenia is associated with organ failure and adverse prognosis. The aetiology for thrombocytopenia in ITU is often multifactorial and correcting one aetiology may not normalise the low platelet count. The classical view for thrombocytopenia in this setting is consumption associated with thrombin-mediated platelet activation, but other concepts, including platelet adhesion to endothelial cells and leucocytes, platelet aggregation by increased von Willebrand factor release, red cell damage and histone release, and platelet destruction by the complement system, have recently been described. The management of severe thrombocytopenia is platelet transfusion in the presence of active bleeding or invasive procedure, but the risk-benefit of prophylactic platelet transfusions in this setting is uncertain. In this review, the incidence and mechanisms of thrombocytopenia in patients with ITU, its prognostic significance and the impact on organ function is discussed. A practical approach based on the authors' experience is described to guide management of a critically ill patient who develops thrombocytopenia. © 2016 John Wiley & Sons Ltd.

Performance recovery of a class of uncertain non-affine systems with unmodelled dynamics: an indirect dynamic inversion method

NASA Astrophysics Data System (ADS)

Yi, Bowen; Lin, Shuyi; Yang, Bo; Zhang, Weidong

2018-02-01

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples.

Finite-time adaptive sliding mode force control for electro-hydraulic load simulator based on improved GMS friction model

NASA Astrophysics Data System (ADS)

Kang, Shuo; Yan, Hao; Dong, Lijing; Li, Changchun

2018-03-01

This paper addresses the force tracking problem of electro-hydraulic load simulator under the influence of nonlinear friction and uncertain disturbance. A nonlinear system model combined with the improved generalized Maxwell-slip (GMS) friction model is firstly derived to describe the characteristics of load simulator system more accurately. Then, by using particle swarm optimization (PSO) algorithm ​combined with the system hysteresis characteristic analysis, the GMS friction parameters are identified. To compensate for nonlinear friction and uncertain disturbance, a finite-time adaptive sliding mode control method is proposed based on the accurate system model. This controller has the ability to ensure that the system state moves along the nonlinear sliding surface to steady state in a short time as well as good dynamic properties under the influence of parametric uncertainties and disturbance, which further improves the force loading accuracy and rapidity. At the end of this work, simulation and experimental results are employed to demonstrate the effectiveness of the proposed sliding mode control strategy.

Adaptive Neural Networks Prescribed Performance Control Design for Switched Interconnected Uncertain Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-06-28

In this paper, an adaptive neural networks (NNs)-based decentralized control scheme with the prescribed performance is proposed for uncertain switched nonstrict-feedback interconnected nonlinear systems. It is assumed that nonlinear interconnected terms and nonlinear functions of the concerned systems are unknown, and also the switching signals are unknown and arbitrary. A linear state estimator is constructed to solve the problem of unmeasured states. The NNs are employed to approximate unknown interconnected terms and nonlinear functions. A new output feedback decentralized control scheme is developed by using the adaptive backstepping design technique. The control design problem of nonlinear interconnected switched systems with unknown switching signals can be solved by the proposed scheme, and only a tuning parameter is needed for each subsystem. The proposed scheme can ensure that all variables of the control systems are semi-globally uniformly ultimately bounded and the tracking errors converge to a small residual set with the prescribed performance bound. The effectiveness of the proposed control approach is verified by some simulation results.

Explicit asymmetric bounds for robust stability of continuous and discrete-time systems

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang; Antsaklis, Panos J.

1993-01-01

The problem of robust stability in linear systems with parametric uncertainties is considered. Explicit stability bounds on uncertain parameters are derived and expressed in terms of linear inequalities for continuous systems, and inequalities with quadratic terms for discrete-times systems. Cases where system parameters are nonlinear functions of an uncertainty are also examined.

Smoothing-based compressed state Kalman filter for joint state-parameter estimation: Applications in reservoir characterization and CO2 storage monitoring

NASA Astrophysics Data System (ADS)

Li, Y. J.; Kokkinaki, Amalia; Darve, Eric F.; Kitanidis, Peter K.

2017-08-01

The operation of most engineered hydrogeological systems relies on simulating physical processes using numerical models with uncertain parameters and initial conditions. Predictions by such uncertain models can be greatly improved by Kalman-filter techniques that sequentially assimilate monitoring data. Each assimilation constitutes a nonlinear optimization, which is solved by linearizing an objective function about the model prediction and applying a linear correction to this prediction. However, if model parameters and initial conditions are uncertain, the optimization problem becomes strongly nonlinear and a linear correction may yield unphysical results. In this paper, we investigate the utility of one-step ahead smoothing, a variant of the traditional filtering process, to eliminate nonphysical results and reduce estimation artifacts caused by nonlinearities. We present the smoothing-based compressed state Kalman filter (sCSKF), an algorithm that combines one step ahead smoothing, in which current observations are used to correct the state and parameters one step back in time, with a nonensemble covariance compression scheme, that reduces the computational cost by efficiently exploring the high-dimensional state and parameter space. Numerical experiments show that when model parameters are uncertain and the states exhibit hyperbolic behavior with sharp fronts, as in CO2 storage applications, one-step ahead smoothing reduces overshooting errors and, by design, gives physically consistent state and parameter estimates. We compared sCSKF with commonly used data assimilation methods and showed that for the same computational cost, combining one step ahead smoothing and nonensemble compression is advantageous for real-time characterization and monitoring of large-scale hydrogeological systems with sharp moving fronts.

Spacecraft Parachute Recovery System Testing from a Failure Rate Perspective

NASA Technical Reports Server (NTRS)

Stewart, Christine E.

2013-01-01

Spacecraft parachute recovery systems, especially those with a parachute cluster, require testing to identify and reduce failures. This is especially important when the spacecraft in question is human-rated. Due to the recent effort to make spaceflight affordable, the importance of determining a minimum requirement for testing has increased. The number of tests required to achieve a mature design, with a relatively constant failure rate, can be estimated from a review of previous complex spacecraft recovery systems. Examination of the Apollo parachute testing and the Shuttle Solid Rocket Booster recovery chute system operation will clarify at which point in those programs the system reached maturity. This examination will also clarify the risks inherent in not performing a sufficient number of tests prior to operation with humans on-board. When looking at complex parachute systems used in spaceflight landing systems, a pattern begins to emerge regarding the need for a minimum amount of testing required to wring out the failure modes and reduce the failure rate of the parachute system to an acceptable level for human spaceflight. Not only a sufficient number of system level testing, but also the ability to update the design as failure modes are found is required to drive the failure rate of the system down to an acceptable level. In addition, sufficient data and images are necessary to identify incipient failure modes or to identify failure causes when a system failure occurs. In order to demonstrate the need for sufficient system level testing prior to an acceptable failure rate, the Apollo Earth Landing System (ELS) test program and the Shuttle Solid Rocket Booster Recovery System failure history will be examined, as well as some experiences in the Orion Capsule Parachute Assembly System will be noted.

Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links.

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

Johnson, Jay Dean; Oberkampf, William Louis; Helton, Jon Craig

2004-12-01

Relationships to determine the probability that a weak link (WL)/strong link (SL) safety system will fail to function as intended in a fire environment are investigated. In the systems under study, failure of the WL system before failure of the SL system is intended to render the overall system inoperational and thus prevent the possible occurrence of accidents with potentially serious consequences. Formal developments of the probability that the WL system fails to deactivate the overall system before failure of the SL system (i.e., the probability of loss of assured safety, PLOAS) are presented for several WWSL configurations: (i) onemore » WL, one SL, (ii) multiple WLs, multiple SLs with failure of any SL before any WL constituting failure of the safety system, (iii) multiple WLs, multiple SLs with failure of all SLs before any WL constituting failure of the safety system, and (iv) multiple WLs, multiple SLs and multiple sublinks in each SL with failure of any sublink constituting failure of the associated SL and failure of all SLs before failure of any WL constituting failure of the safety system. The indicated probabilities derive from time-dependent temperatures in the WL/SL system and variability (i.e., aleatory uncertainty) in the temperatures at which the individual components of this system fail and are formally defined as multidimensional integrals. Numerical procedures based on quadrature (i.e., trapezoidal rule, Simpson's rule) and also on Monte Carlo techniques (i.e., simple random sampling, importance sampling) are described and illustrated for the evaluation of these integrals. Example uncertainty and sensitivity analyses for PLOAS involving the representation of uncertainty (i.e., epistemic uncertainty) with probability theory and also with evidence theory are presented.« less

Control and modeling of a CELSS (Controlled Ecological Life Support System)

NASA Technical Reports Server (NTRS)

Auslander, D. M.; Spear, R. C.; Babcock, P. S.; Nadel, M.

1983-01-01

Research topics that arise from the conceptualization of control for closed life support systems which are life support systems in which all or most of the mass is recycled are discussed. Modeling and control of uncertain and poorly defined systems, resource allocation in closed life support systems, and control structures or systems with delay and closure are emphasized.

Heroic Reliability Improvement in Manned Space Systems

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2017-01-01

System reliability can be significantly improved by a strong continued effort to identify and remove all the causes of actual failures. Newly designed systems often have unexpected high failure rates which can be reduced by successive design improvements until the final operational system has an acceptable failure rate. There are many causes of failures and many ways to remove them. New systems may have poor specifications, design errors, or mistaken operations concepts. Correcting unexpected problems as they occur can produce large early gains in reliability. Improved technology in materials, components, and design approaches can increase reliability. The reliability growth is achieved by repeatedly operating the system until it fails, identifying the failure cause, and fixing the problem. The failure rate reduction that can be obtained depends on the number and the failure rates of the correctable failures. Under the strong assumption that the failure causes can be removed, the decline in overall failure rate can be predicted. If a failure occurs at the rate of lambda per unit time, the expected time before the failure occurs and can be corrected is 1/lambda, the Mean Time Before Failure (MTBF). Finding and fixing a less frequent failure with the rate of lambda/2 per unit time requires twice as long, time of 1/(2 lambda). Cutting the failure rate in half requires doubling the test and redesign time and finding and eliminating the failure causes.Reducing the failure rate significantly requires a heroic reliability improvement effort.

Final Report. Analysis and Reduction of Complex Networks Under Uncertainty

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

Marzouk, Youssef M.; Coles, T.; Spantini, A.

2013-09-30

The project was a collaborative effort among MIT, Sandia National Laboratories (local PI Dr. Habib Najm), the University of Southern California (local PI Prof. Roger Ghanem), and The Johns Hopkins University (local PI Prof. Omar Knio, now at Duke University). Our focus was the analysis and reduction of large-scale dynamical systems emerging from networks of interacting components. Such networks underlie myriad natural and engineered systems. Examples important to DOE include chemical models of energy conversion processes, and elements of national infrastructure—e.g., electric power grids. Time scales in chemical systems span orders of magnitude, while infrastructure networks feature both local andmore » long-distance connectivity, with associated clusters of time scales. These systems also blend continuous and discrete behavior; examples include saturation phenomena in surface chemistry and catalysis, and switching in electrical networks. Reducing size and stiffness is essential to tractable and predictive simulation of these systems. Computational singular perturbation (CSP) has been effectively used to identify and decouple dynamics at disparate time scales in chemical systems, allowing reduction of model complexity and stiffness. In realistic settings, however, model reduction must contend with uncertainties, which are often greatest in large-scale systems most in need of reduction. Uncertainty is not limited to parameters; one must also address structural uncertainties—e.g., whether a link is present in a network—and the impact of random perturbations, e.g., fluctuating loads or sources. Research under this project developed new methods for the analysis and reduction of complex multiscale networks under uncertainty, by combining computational singular perturbation (CSP) with probabilistic uncertainty quantification. CSP yields asymptotic approximations of reduceddimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty in this context raised fundamentally new issues, e.g., how is the topology of slow manifolds transformed by parametric uncertainty? How to construct dynamical models on these uncertain manifolds? To address these questions, we used stochastic spectral polynomial chaos (PC) methods to reformulate uncertain network models and analyzed them using CSP in probabilistic terms. Finding uncertain manifolds involved the solution of stochastic eigenvalue problems, facilitated by projection onto PC bases. These problems motivated us to explore the spectral properties stochastic Galerkin systems. We also introduced novel methods for rank-reduction in stochastic eigensystems—transformations of a uncertain dynamical system that lead to lower storage and solution complexity. These technical accomplishments are detailed below. This report focuses on the MIT portion of the joint project.« less

A hazard and risk classification system for catastrophic rock slope failures in Norway

NASA Astrophysics Data System (ADS)

Hermanns, R.; Oppikofer, T.; Anda, E.; Blikra, L. H.; Böhme, M.; Bunkholt, H.; Dahle, H.; Devoli, G.; Eikenæs, O.; Fischer, L.; Harbitz, C. B.; Jaboyedoff, M.; Loew, S.; Yugsi Molina, F. X.

2012-04-01

The Geological Survey of Norway carries out systematic geologic mapping of potentially unstable rock slopes in Norway that can cause a catastrophic failure. As catastrophic failure we describe failures that involve substantial fragmentation of the rock mass during run-out and that impact an area larger than that of a rock fall (shadow angle of ca. 28-32° for rock falls). This includes therefore rock slope failures that lead to secondary effects, such as a displacement wave when impacting a water body or damming of a narrow valley. Our systematic mapping revealed more than 280 rock slopes with significant postglacial deformation, which might represent localities of large future rock slope failures. This large number necessitates prioritization of follow-up activities, such as more detailed investigations, periodic monitoring and permanent monitoring and early-warning. In the past hazard and risk were assessed qualitatively for some sites, however, in order to compare sites so that political and financial decisions can be taken, it was necessary to develop a quantitative hazard and risk classification system. A preliminary classification system was presented and discussed with an expert group of Norwegian and international experts and afterwards adapted following their recommendations. This contribution presents the concept of this final hazard and risk classification that should be used in Norway in the upcoming years. Historical experience and possible future rockslide scenarios in Norway indicate that hazard assessment of large rock slope failures must be scenario-based, because intensity of deformation and present displacement rates, as well as the geological structures activated by the sliding rock mass can vary significantly on a given slope. In addition, for each scenario the run-out of the rock mass has to be evaluated. This includes the secondary effects such as generation of displacement waves or landslide damming of valleys with the potential of later outburst floods. It became obvious that large rock slope failures cannot be evaluated on a slope scale with frequency analyses of historical and prehistorical events only, as multiple rockslides have occurred within one century on a single slope that prior to the recent failures had been inactive for several thousand years. In addition, a systematic analysis on temporal distribution indicates that rockslide activity following deglaciation after the Last Glacial Maximum has been much higher than throughout the Holocene. Therefore the classification system has to be based primarily on the geological conditions on the deforming slope and on the deformation rates and only to a lesser weight on a frequency analyses. Our hazard classification therefore is primarily based on several criteria: 1) Development of the back-scarp, 2) development of the lateral release surfaces, 3) development of the potential basal sliding surface, 4) morphologic expression of the basal sliding surface, 5) kinematic feasibility tests for different displacement mechanisms, 6) landslide displacement rates, 7) change of displacement rates (acceleration), 8) increase of rockfall activity on the unstable rock slope, 9) Presence post-glacial events of similar size along the affected slope and its vicinity. For each of these criteria several conditions are possible to choose from (e.g. different velocity classes for the displacement rate criterion). A score is assigned to each condition and the sum of all scores gives the total susceptibility score. Since many of these observations are somewhat uncertain, the classification system is organized in a decision tree where probabilities can be assigned to each condition. All possibilities in the decision tree are computed and the individual probabilities giving the same total score are summed. Basic statistics show the minimum and maximum total scores of a scenario, as well as the mean and modal value. The final output is a cumulative frequency distribution of the susceptibility scores that can be divided into several classes, which are interpreted as susceptibility classes (very high, high, medium, low, and very low). Today the Norwegian Planning and Building Act uses hazard classes with annual probabilities of impact on buildings producing damages (<1/100, <1/1000, <1/5000 and zero for critical buildings). However, up to now there is not enough scientific knowledge to predict large rock slope failures in these strict classes. Therefore, the susceptibility classes will be matched with the hazard classes from the Norwegian Building Act (e.g. very high susceptibility represents the hazard class with annual probability >1/100). The risk analysis focuses on the potential fatalities of a worst case rock slide scenario and its secondary effects only and is done in consequence classes with a decimal logarithmic scale. However we recommend for all high risk objects that municipalities carry out detailed risk analyses. Finally, the hazard and risk classification system will give recommendations where surveillance in form of continuous 24/7 monitoring systems coupled with early-warning systems (high risk class) or periodic monitoring (medium risk class) should be carried out. These measures are understood as to reduce the risk of life loss due to a rock slope failure close to 0 as population can be evacuated on time if a change of stability situation occurs. The final hazard and risk classification for all potentially unstable rock slopes in Norway, including all data used for its classification will be published within the national landslide database (available on www.skrednett.no).

Real time health monitoring and control system methodology for flexible space structures

NASA Astrophysics Data System (ADS)

Jayaram, Sanjay

This dissertation is concerned with the Near Real-time Autonomous Health Monitoring of Flexible Space Structures. The dynamics of multi-body flexible systems is uncertain due to factors such as high non-linearity, consideration of higher modal frequencies, high dimensionality, multiple inputs and outputs, operational constraints, as well as unexpected failures of sensors and/or actuators. Hence a systematic framework of developing a high fidelity, dynamic model of a flexible structural system needs to be understood. The fault detection mechanism that will be an integrated part of an autonomous health monitoring system comprises the detection of abnormalities in the sensors and/or actuators and correcting these detected faults (if possible). Applying the robust control law and the robust measures that are capable of detecting and recovering/replacing the actuators rectifies the actuator faults. The fault tolerant concept applied to the sensors will be in the form of an Extended Kalman Filter (EKF). The EKF is going to weigh the information coming from multiple sensors (redundant sensors used to measure the same information) and automatically identify the faulty sensors and weigh the best estimate from the remaining sensors. The mechanization is comprised of instrumenting flexible deployable panels (solar array) with multiple angular position and rate sensors connected to the data acquisition system. The sensors will give position and rate information of the solar panel in all three axes (i.e. roll, pitch and yaw). The position data corresponds to the steady state response and the rate data will give better insight on the transient response of the system. This is a critical factor for real-time autonomous health monitoring. MATLAB (and/or C++) software will be used for high fidelity modeling and fault tolerant mechanism.

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

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

Hodge, B. M.; Florita, A.; Orwig, K.

2012-07-01

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent Systemmore » Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.« less

Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

PubMed

Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

2014-08-01

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

A novel adaptive switching function on fault tolerable sliding mode control for uncertain stochastic systems.

PubMed

Zahiripour, Seyed Ali; Jalali, Ali Akbar

2014-09-01

A novel switching function based on an optimization strategy for the sliding mode control (SMC) method has been provided for uncertain stochastic systems subject to actuator degradation such that the closed-loop system is globally asymptotically stable with probability one. In the previous researches the focus on sliding surface has been on proportional or proportional-integral function of states. In this research, from a degree of freedom that depends on designer choice is used to meet certain objectives. In the design of the switching function, there is a parameter which the designer can regulate for specified objectives. A sliding-mode controller is synthesized to ensure the reachability of the specified switching surface, despite actuator degradation and uncertainties. Finally, the simulation results demonstrate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Integral Sliding Mode Fault-Tolerant Control for Uncertain Linear Systems Over Networks With Signals Quantization.

PubMed

Hao, Li-Ying; Park, Ju H; Ye, Dan

2017-09-01

In this paper, a new robust fault-tolerant compensation control method for uncertain linear systems over networks is proposed, where only quantized signals are assumed to be available. This approach is based on the integral sliding mode (ISM) method where two kinds of integral sliding surfaces are constructed. One is the continuous-state-dependent surface with the aim of sliding mode stability analysis and the other is the quantization-state-dependent surface, which is used for ISM controller design. A scheme that combines the adaptive ISM controller and quantization parameter adjustment strategy is then proposed. Through utilizing H ∞ control analytical technique, once the system is in the sliding mode, the nature of performing disturbance attenuation and fault tolerance from the initial time can be found without requiring any fault information. Finally, the effectiveness of our proposed ISM control fault-tolerant schemes against quantization errors is demonstrated in the simulation.

Conflict management based on belief function entropy in sensor fusion.

PubMed

Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

2016-01-01

Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods.

Probability of loss of assured safety in systems with multiple time-dependent failure modes.

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

Helton, Jon Craig; Pilch, Martin.; Sallaberry, Cedric Jean-Marie.

2012-09-01

Weak link (WL)/strong link (SL) systems are important parts of the overall operational design of high-consequence systems. In such designs, the SL system is very robust and is intended to permit operation of the entire system under, and only under, intended conditions. In contrast, the WL system is intended to fail in a predictable and irreversible manner under accident conditions and render the entire system inoperable before an accidental operation of the SL system. The likelihood that the WL system will fail to deactivate the entire system before the SL system fails (i.e., degrades into a configuration that could allowmore » an accidental operation of the entire system) is referred to as probability of loss of assured safety (PLOAS). Representations for PLOAS for situations in which both link physical properties and link failure properties are time-dependent are derived and numerically evaluated for a variety of WL/SL configurations, including PLOAS defined by (i) failure of all SLs before failure of any WL, (ii) failure of any SL before failure of any WL, (iii) failure of all SLs before failure of all WLs, and (iv) failure of any SL before failure of all WLs. The effects of aleatory uncertainty and epistemic uncertainty in the definition and numerical evaluation of PLOAS are considered.« less

Financial arrangements for health systems in low-income countries: an overview of systematic reviews

PubMed Central

Wiysonge, Charles S; Paulsen, Elizabeth; Lewin, Simon; Ciapponi, Agustín; Herrera, Cristian A; Opiyo, Newton; Pantoja, Tomas; Rada, Gabriel; Oxman, Andrew D

2017-01-01

Background One target of the Sustainable Development Goals is to achieve "universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for all". A fundamental concern of governments in striving for this goal is how to finance such a health system. This concern is very relevant for low-income countries. Objectives To provide an overview of the evidence from up-to-date systematic reviews about the effects of financial arrangements for health systems in low-income countries. Secondary objectives include identifying needs and priorities for future evaluations and systematic reviews on financial arrangements, and informing refinements in the framework for financial arrangements presented in the overview. Methods We searched Health Systems Evidence in November 2010 and PDQ-Evidence up to 17 December 2016 for systematic reviews. We did not apply any date, language, or publication status limitations in the searches. We included well-conducted systematic reviews of studies that assessed the effects of financial arrangements on patient outcomes (health and health behaviours), the quality or utilisation of healthcare services, resource use, healthcare provider outcomes (such as sick leave), or social outcomes (such as poverty, employment, or financial burden of patients, e.g. out-of-pocket payment, catastrophic disease expenditure) and that were published after April 2005. We excluded reviews with limitations important enough to compromise the reliability of the findings. Two overview authors independently screened reviews, extracted data, and assessed the certainty of evidence using GRADE. We prepared SUPPORT Summaries for eligible reviews, including key messages, 'Summary of findings' tables (using GRADE to assess the certainty of the evidence), and assessments of the relevance of findings to low-income countries. Main results We identified 7272 reviews and included 15 in this overview, on: collection of funds (2 reviews), insurance schemes (1 review), purchasing of services (1 review), recipient incentives (6 reviews), and provider incentives (5 reviews). The reviews were published between 2008 and 2015; focused on 13 subcategories; and reported results from 276 studies: 115 (42%) randomised trials, 11 (4%) non-randomised trials, 23 (8%) controlled before-after studies, 51 (19%) interrupted time series, 9 (3%) repeated measures, and 67 (24%) other non-randomised studies. Forty-three per cent (119/276) of the studies included in the reviews took place in low- and middle-income countries. Collection of funds: the effects of changes in user fees on utilisation and equity are uncertain (very low-certainty evidence). It is also uncertain whether aid delivered under the Paris Principles (ownership, alignment, harmonisation, managing for results, and mutual accountability) improves health outcomes compared to aid delivered without conforming to those principles (very low-certainty evidence). Insurance schemes: community-based health insurance may increase service utilisation (low-certainty evidence), but the effects on health outcomes are uncertain (very low-certainty evidence). It is uncertain whether social health insurance improves utilisation of health services or health outcomes (very low-certainty evidence). Purchasing of services: it is uncertain whether increasing salaries of public sector healthcare workers improves the quantity or quality of their work (very low-certainty evidence). Recipient incentives: recipient incentives may improve adherence to long-term treatments (low-certainty evidence), but it is uncertain whether they improve patient outcomes. One-time recipient incentives probably improve patient return for start or continuation of treatment (moderate-certainty evidence) and may improve return for tuberculosis test readings (low-certainty evidence). However, incentives may not improve completion of tuberculosis prophylaxis, and it is uncertain whether they improve completion of treatment for active tuberculosis. Conditional cash transfer programmes probably lead to an increase in service utilisation (moderate-certainty evidence), but their effects on health outcomes are uncertain. Vouchers may improve health service utilisation (low-certainty evidence), but the effects on health outcomes are uncertain (very low-certainty evidence). Introducing a restrictive cap may decrease use of medicines for symptomatic conditions and overall use of medicines, may decrease insurers' expenditures on medicines (low-certainty evidence), and has uncertain effects on emergency department use, hospitalisations, and use of outpatient care (very low-certainty evidence). Reference pricing, maximum pricing, and index pricing for drugs have mixed effects on drug expenditures by patients and insurers as well as the use of brand and generic drugs. Provider incentives: the effects of provider incentives are uncertain (very low-certainty evidence), including: the effects of provider incentives on the quality of care provided by primary care physicians or outpatient referrals from primary to secondary care, incentives for recruiting and retaining health professionals to serve in remote areas, and the effects of pay-for-performance on provider performance, the utilisation of services, patient outcomes, or resource use in low-income countries. Authors' conclusions Research based on sound systematic review methods has evaluated numerous financial arrangements relevant to low-income countries, targeting different levels of the health systems and assessing diverse outcomes. However, included reviews rarely reported social outcomes, resource use, equity impacts, or undesirable effects. We also identified gaps in primary research because of uncertainty about applicability of the evidence to low-income countries. Financial arrangements for which the effects are uncertain include external funding (aid), caps and co-payments, pay-for-performance, and provider incentives. Further studies evaluating the effects of these arrangements are needed in low-income countries. Systematic reviews should include all outcomes that are relevant to decision-makers and to people affected by changes in financial arrangements. Financial arrangements for health systems in low-income countries What is the aim of this overview? The aim of this Cochrane Overview is to provide a broad summary of what is known about the effects of financial arrangements for health systems in low-income countries. This overview is based on 15 systematic reviews. Each of these systematic reviews searched for studies that evaluated different types of financial arrangements within the scope of the review question. The reviews included a total of 276 studies. This overview is one of a series of four Cochrane Overviews that evaluate different health system arrangements. Main results What are the effects of different ways of collecting funds to pay for health services? Two reviews looked for studies that addressed this question and found the following. - The effects of changes in user fees on utilisation and equity are uncertain (very low-certainty evidence). - It is uncertain whether aid delivered under Paris Principles (ownership, alignment, harmonisation, managing for results, and mutual accountability) improves health compared to aid delivered without conforming to those principles (very low-certainty evidence). What are the effects of different types of insurance schemes? One systematic review looked for studies that addressed this question and found the following. - Community-based health insurance may increase people's use of services (low-certainty evidence), but the effects on people's health are uncertain. It is uncertain whether social health insurance increases people's use of services (very low-certainty evidence). What are the effects of different ways of paying for health services? One systematic review looked for studies that addressed this question and found the following. - It is uncertain whether increasing salaries of public sector healthcare workers improves the quantity or quality of their work. What are the effects of different types of financial incentives for recipients of care? Six systematic reviews looked for studies that addressed this question and found the following. - Giving healthcare recipients incentives may improve their adherence to long-term treatments (low-certainty evidence), but it is uncertain whether they improve people's health. - Giving healthcare recipients one-time incentives probably leads more people to return to start or continue treatment for tuberculosis (moderate-certainty evidence). The certainty of the evidence for other types of recipient incentives for tuberculosis is low or very low. - Conditional cash transfer programmes (giving money to recipients of care on the condition that they take a specified action to improve their health) probably increase people's use of services (moderate-certainty evidence), but have mixed effect on people's health. - Vouchers may improve people's use of health services (low-certainty evidence) but have mixed effects on people's health (low-certainty evidence). - A combination of a ceiling and co-insurance probably slightly decreases the overall use of medicines (moderate-certainty evidence) and may increase health service utilisation (low-certainty evidence). The certainty of the evidence for the effects of other combinations of caps, co-insurance, co-payments, and ceilings is low or very low. - Limits on how much insurers pay for different groups of drugs (reference pricing, maximum pricing, and index pricing) have mixed effects on drug expenditures by patients and insurers as well as the use of brand and generic drugs. What are the effects of different types of financial incentives for health workers? Five systematic reviews looked for studies that addressed this question and found the following. - We are uncertain whether pay-for-performance improves health worker performance, people's use of services, people's health, or resource use in low-income countries (very low-certainty evidence). - We are uncertain whether financial incentives for health workers improve the quality of care provided by primary care physicians or outpatient referrals from primary to secondary care (very low-certainty evidence). - There is no rigorous research evaluating incentives (e.g. bursaries or scholarships linked to future practice location, rural allowances) for recruiting health workers to serve in remote areas. It is uncertain whether giving health workers incentives lead more of them to stay in underserved areas (very low-certainty evidence). - No studies assessed the effects of financial interventions on the movement of health workers between public and private organisations in low- and middle-income countries. How up to date is this overview? The overview authors searched for systematic reviews published up to 17 December 2016. PMID:28891235

Risk Based Reliability Centered Maintenance of DOD Fire Protection Systems

DTIC Science & Technology

1999-01-01

2.2.3 Failure Mode and Effect Analysis ( FMEA )............................ 2.2.4 Failure Mode Risk Characterization...Step 2 - System functions and functional failures definition Step 3 - Failure mode and effect analysis ( FMEA ) Step 4 - Failure mode risk...system). The Interface Location column identifies the location where the FMEA of the fire protection system began or stopped. For example, for the fire

Quality Issues in Propulsion

NASA Technical Reports Server (NTRS)

McCarty, John P.; Lyles, Garry M.

1997-01-01

Propulsion system quality is defined in this paper as having high reliability, that is, quality is a high probability of within-tolerance performance or operation. Since failures are out-of-tolerance performance, the probability of failures and their occurrence is the difference between high and low quality systems. Failures can be described at 3 levels: the system failure (which is the detectable end of a failure), the failure mode (which is the failure process), and the failure cause (which is the start). Failure causes can be evaluated & classified by type. The results of typing flight history failures shows that most failures are in unrecognized modes and result from human error or noise, i.e. failures are when engineers learn how things really work. Although the study based on US launch vehicles, a sampling of failures from other countries indicates the finding has broad application. The parameters of the design of a propulsion system are not single valued, but have dispersions associated with the manufacturing of parts. Many tests are needed to find failures, if the dispersions are large relative to tolerances, which could contribute to the large number of failures in unrecognized modes.

USAF Evaluation of an Automated Adaptive Flight Training System

DTIC Science & Technology

1975-10-01

system. C. What is the most effective wav to utilize the system in ^jierational training’ Student opinion for this question JS equally divided...None Utility hydraulic failure Flap failure left engine failure Right engine failure Stah 2 aug failure No g\\ ro approach procedure, no MIDI

Safety and efficacy of empirical interleukin-1 inhibition using anakinra in AA amyloidosis of uncertain aetiology.

PubMed

Lane, Thirusha; Wechalekar, Ashutosh D; Gillmore, Julian D; Hawkins, Philip N; Lachmann, Helen J

2017-09-01

AA amyloidosis is a serious complication of persistent inflammation, which, untreated will progress to renal failure and death. Effective suppression of the underlying inflammatory disease is the focus of treatment. However, in approximately 20% of cases the underlying condition remains uncertain, presenting a dilemma as to choice of treatment. We conducted a retrospective study of a cohort of 11 patients diagnosed with AA amyloidosis of unknown aetiology, who had been empirically treated with anakinra. In anakinra-responders, median pre-treatment SAA was 74 (IQR 34-190) mg/L, and median on-treatment SAA was 6 (4-16) mg/L (p = .0047), with the response having been maintained for a median on-treatment follow-up of 1.8 (1-7.6) years. Six dialysis patients were treated effectively and safely with 100 mg anakinra three times weekly post-dialysis. Four patients remained well on daily anakinra post-renal transplant. Five anakinra-responders showed regression and three showed stabilization of amyloid load on serial SAP scintigraphy. This small cohort shows that even in potentially high risk cases with organ damage secondary to AA amyloidosis or in the presence of a renal graft, anakinra, when used appropriately and carefully monitored, has proved remarkably effective and well tolerated. Longer follow-up of this off-label use is required.

Chronic kidney disease of uncertain etiology in Sri Lanka: Are leptospirosis and Hantaviral infection likely causes?

PubMed

Gamage, Chandika Damesh; Sarathkumara, Yomani Dilukshi

2016-06-01

Chronic kidney disease of uncertain etiology (CKDu) has been a severe burden and a public health crisis in Sri Lanka over the past two decades. Many studies have established hypotheses to identify potential risk factors although causative agents, risk factors and etiology of this disease are still uncertain. Several studies have postulated that fungal and bacterial nephrotoxins are a possible etiological factor; however, the precise link between hypothesized risk factors and the pathogenesis of chronic kidney disease has yet to be proven in prior studies. Leptospirosis and Hantavirus infections are important zoonotic diseases that are naturally maintained and transmitted via infected rodent populations and which present similar clinical and epidemiological features. Both infections are known to be a cause of acute kidney damage that can proceed into chronic renal failure. Several studies have reported presence of both infections in Sri Lanka. Therefore, we hypothesized that pathogenic Leptospira or Hantavirus are possible causative agents of acute kidney damage which eventually progresses to chronic kidney disease in Sri Lanka. The proposed hypothesis will be evaluated by means of an observational study design. Past infection will be assessed by a cross-sectional study to detect the presence of IgG antibodies with further confirmatory testing among chronic kidney disease patients and individuals from the community in selected endemic areas compared to low prevalence areas. Identification of possible risk factors for these infections will be followed by a case-control study and causality will be further determined with a cohort study. If the current hypothesis is true, affected communities will be subjected for medical interventions related to the disease for patient management while considering supportive therapies. Furthermore and possibly enhance their preventive and control measures to improve vector control to decrease the risk of infection. Copyright © 2016 Elsevier Ltd. All rights reserved.

ACCF/SCAI/AATS/AHA/ASE/ASNC/HFSA/HRS/SCCM/SCCT/SCMR/STS 2012 appropriate use criteria for diagnostic catheterization: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, Society for Cardiovascular Angiography and Interventions, American Association for Thoracic Surgery, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society of Critical Care Medicine, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons.

PubMed

Patel, Manesh R; Bailey, Steven R; Bonow, Robert O; Chambers, Charles E; Chan, Paul S; Dehmer, Gregory J; Kirtane, Ajay J; Wann, L Samuel; Ward, R Parker

2012-05-29

The American College of Cardiology Foundation, in collaboration with the Society for Cardiovascular Angiography and Interventions and key specialty and subspecialty societies, conducted a review of common clinical scenarios where diagnostic catheterization is frequently considered. The indications (clinical scenarios) were derived from common applications or anticipated uses, as well as from current clinical practice guidelines and results of studies examining the implementation of noninvasive imaging appropriate use criteria. The 166 indications in this document were developed by a diverse writing group and scored by a separate independent technical panel on a scale of 1 to 9, to designate appropriate use (median 7 to 9), uncertain use (median 4 to 6), and inappropriate use (median 1 to 3). Diagnostic catheterization may include several different procedure components. The indications developed focused primarily on 2 aspects of diagnostic catheterization. Many indications focused on the performance of coronary angiography for the detection of coronary artery disease with other procedure components (e.g., hemodynamic measurements, ventriculography) at the discretion of the operator. The majority of the remaining indications focused on hemodynamic measurements to evaluate valvular heart disease, pulmonary hypertension, cardiomyopathy, and other conditions, with the use of coronary angiography at the discretion of the operator. Seventy-five indications were rated as appropriate, 49 were rated as uncertain, and 42 were rated as inappropriate. The appropriate use criteria for diagnostic catheterization have the potential to impact physician decision making, healthcare delivery, and reimbursement policy. Furthermore, recognition of uncertain clinical scenarios facilitates identification of areas that would benefit from future research.

[Clinical characteristics, complications and mortality in 506 patients with infective endocarditis and determinants of survival rate at 10 years].

PubMed

Oyonarte, Miguel; Montagna, Rodrigo; Braun, Sandra; Rojo, Pamela; Jara, José L; Cereceda, Mauricio; Morales, Marcelo; Nazzal, Carolina; Nazal, Carolina; Alonso, Faustino

2012-12-01

Rates of morbidity and mortality in Infective Endocarditis (IE) remain high and prognosis in this disease is still difficult and uncertain. To study IE in Chile in its active phase during inpatient hospital stay and long term survival rates. Observational prospective national cohort study of 506 consecutive patients included between June 1,1998 and July 31, 2008, from 37 Chilean hospitals (secondary and tertiary centers) nationwide. The main findings were the presence of Rheumatic valve disease in 22.1 % of patients, a history of intravenous drug abuse (IVDA) only in 0.7%, the presence of Staphylococcus aureus in 29.2% of blood cultures, negative blood cultures in 33.2%, heart failure in 51.7% and native valve involvement in 86% of patients. Echocardiographic diagnosis was achieved in 94% of patients. Hospital mortality was 26.1% and its prognostics factors were persisting infection (Odds ratio (OR) 6.43, Confidence Interval (CI) 1.45-28.33%), failure of medical treatment and no surgical intervention (OR 48.8; CI 6.67-349.9). Five and 10 years survival rates were 75.6 and 48.6%, respectively. The significant prognostic factors for long term mortality, determined by multivariate analysis were the presence of diabetes, Staphylococcus aureus infection, sepsis, heart failure, renal failure and lack of surgical treatment during the IE episode. The microbiologic diagnosis of IE must be urgently improved in Chile. Mortality rates are still high (26.1%) partly because of a high incidence of negative blood cultures and the need for more surgical valve interventions during in-hospital period. Long term prognostic factors for mortality should be identified early to improve outcome.

Assessing the impact of heart failure specialist services on patient populations.

PubMed

Lyratzopoulos, Georgios; Cook, Gary A; McElduff, Patrick; Havely, Daniel; Edwards, Richard; Heller, Richard F

2004-05-24

The assessment of the impact of healthcare interventions may help commissioners of healthcare services to make optimal decisions. This can be particularly the case if the impact assessment relates to specific patient populations and uses timely local data. We examined the potential impact on readmissions and mortality of specialist heart failure services capable of delivering treatments such as b-blockers and Nurse-Led Educational Intervention (N-LEI). Statistical modelling of prevented or postponed events among previously hospitalised patients, using estimates of: treatment uptake and contraindications (based on local audit data); treatment effectiveness and intolerance (based on literature); and annual number of hospitalization per patient and annual risk of death (based on routine data). Optimal treatment uptake among eligible but untreated patients would over one year prevent or postpone 11% of all expected readmissions and 18% of all expected deaths for spironolactone, 13% of all expected readmisisons and 22% of all expected deaths for b-blockers (carvedilol) and 20% of all expected readmissions and an uncertain number of deaths for N-LEI. Optimal combined treatment uptake for all three interventions during one year among all eligible but untreated patients would prevent or postpone 37% of all expected readmissions and a minimum of 36% of all expected deaths. In a population of previously hospitalised patients with low previous uptake of b-blockers and no uptake of N-LEI, optimal combined uptake of interventions through specialist heart failure services can potentially help prevent or postpone approximately four times as many readmissions and a minimum of twice as many deaths compared with simply optimising uptake of spironolactone (not necessarily requiring specialist services). Examination of the impact of different heart failure interventions can inform rational planning of relevant healthcare services.

Should heart failure be regarded as a terminal illness requiring palliative care? A study of heart failure patients', carers' and clinicians' understanding of heart failure prognosis and its management.

PubMed

Stocker, Rachel; Close, Helen; Hancock, Helen; Hungin, A Pali S

2017-12-01

Communication and planning for heart failure (HF) care near the end of life is known to be complex. Little is known about how the patient experience of palliative assessment and communication needs change over time, and how this might inform management. Our aim was to explore experiences of giving or receiving a prognosis and advanced palliative care planning (ACP) for those with HF. We carried out a longitudinal grounded theory study, employing in-depth interviews with 14 clinicians (primary and secondary care) and observations of clinic and home appointments, followed by a series of interviews with 13 patients with HF and 9 carers. Overall, the majority of participants rejected notions of HF as a terminal illness in favour of a focus on day-to-day management and maintenance, despite obvious deterioration in disease stage and needs over time. Clinicians revealed frustration about the uncertain nature of HF prognosis, leading to difficulties in planning. Others highlighted the need to deliver problem-based, individualised care but felt constrained sometimes by the lack of multidisciplinary ACP. Patients reported an absence of prognostic discussions with clinicians. This is the first study exploring the experiences of prognostic communication at all stages of HF. Findings raise questions regarding the pragmatic utility of the concept of HF as a terminal illness and have implications for future HF care pathway development. Findings support the incorporation of a problem-based approach to management, which recognises the importance of everyday functioning for patients and carers as well as the opportunity for ACP. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

What proportion of patients with chronic heart failure are eligible for sacubitril-valsartan?

PubMed

Pellicori, Pierpaolo; Urbinati, Alessia; Shah, Parin; MacNamara, Alexandra; Kazmi, Syed; Dierckx, Riet; Zhang, Jufen; Cleland, John G F; Clark, Andrew L

2017-06-01

The PARADIGM-HF trial showed that sacubitril-valsartan, an ARB-neprilysin inhibitor, is more effective than enalapril for some patients with heart failure (HF). It is uncertain what proportion of patients with HF would be eligible for sacubitril-valsartan in clinical practice. Between 2001 and 2014, 6131 patients consecutively referred to a community HF clinic with suspected HF were assessed. The criteria required to enter the randomized phase of PARADIGM-HF, including symptoms, NT-proBNP, and current treatment with or without target doses of ACE inhibitors or ARBs, were applied to identify the proportion of patients eligible for sacubitril-valsartan. Recognizing the diversity of clinical opinion and guideline recommendations concerning this issue, entry criteria were applied singly and in combination. Of 1396 patients with reduced left ventricular ejection fraction (≤40%, HFrEF) and contemporary measurement of NT-proBNP, 379 were on target doses of an ACE inhibitor or ARB at their initial visit and, of these, 172 (45%) fulfilled the key entry criteria for the PARADIGM-HF trial. Lack of symptoms (32%) and NT-proBNP <600 ng/L (49%) were common reasons for failure to fulfil criteria. A further 122 patients became eligible during follow-up (n = 294, 21%). However, if background medication and doses were ignored, then 701 (50%) were eligible initially and a further 137 became eligible during follow-up. Of patients with HFrEF referred to a clinic such as ours, only 21% fulfilled the PARADIGM-HF randomization criteria, on which the ESC Guidelines are based; this proportion rises to 60% if background medication is ignored. © 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.

Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

USDA-ARS?s Scientific Manuscript database

Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest ...

A game theoretic controller for a linear time-invariant system with parameter uncertainty and its application to the Space Station

NASA Technical Reports Server (NTRS)

Rhee, Ihnseok; Speyer, Jason L.

1990-01-01

A game theoretic controller is developed for a linear time-invariant system with parameter uncertainties in system and input matrices. The input-output decomposition modeling for the plant uncertainty is adopted. The uncertain dynamic system is represented as an internal feedback loop in which the system is assumed forced by fictitious disturbance caused by the parameter uncertainty. By considering the input and the fictitious disturbance as two noncooperative players, a differential game problem is constructed. It is shown that the resulting time invariant controller stabilizes the uncertain system for a prescribed uncertainty bound. This game theoretic controller is applied to the momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Inclusion of the external disturbance torque to the design procedure results in a dynamical feedback controller which consists of conventional PID control and cyclic disturbance rejection filter. It is shown that the game theoretic design, comparing to the LQR design or pole placement design, improves the stability robustness with respect to inertia variations.

Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems

NASA Technical Reports Server (NTRS)

Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.

2005-01-01

The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

CPLOAS_2 user manual

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

Sallaberry, Cedric Jean-Marie.; Helton, Jon Craig

2012-10-01

Weak link (WL)/strong link (SL) systems are important parts of the overall operational design of high-consequence systems. In such designs, the SL system is very robust and is intended to permit operation of the entire system under, and only under, intended conditions. In contrast, the WL system is intended to fail in a predictable and irreversible manner under accident conditions and render the entire system inoperable before an accidental operation of the SL system. The likelihood that the WL system will fail to deactivate the entire system before the SL system fails (i.e., degrades into a configuration that could allowmore » an accidental operation of the entire system) is referred to as probability of loss of assured safety (PLOAS). This report describes the Fortran 90 program CPLOAS_2 that implements the following representations for PLOAS for situations in which both link physical properties and link failure properties are time-dependent: (i) failure of all SLs before failure of any WL, (ii) failure of any SL before failure of any WL, (iii) failure of all SLs before failure of all WLs, and (iv) failure of any SL before failure of all WLs. The effects of aleatory uncertainty and epistemic uncertainty in the definition and numerical evaluation of PLOAS can be included in the calculations performed by CPLOAS_2.« less

Program Helps In Analysis Of Failures

NASA Technical Reports Server (NTRS)

Stevenson, R. W.; Austin, M. E.; Miller, J. G.

1993-01-01

Failure Environment Analysis Tool (FEAT) computer program developed to enable people to see and better understand effects of failures in system. User selects failures from either engineering schematic diagrams or digraph-model graphics, and effects or potential causes of failures highlighted in color on same schematic-diagram or digraph representation. Uses digraph models to answer two questions: What will happen to system if set of failure events occurs? and What are possible causes of set of selected failures? Helps design reviewers understand exactly what redundancies built into system and where there is need to protect weak parts of system or remove them by redesign. Program also useful in operations, where it helps identify causes of failure after they occur. FEAT reduces costs of evaluation of designs, training, and learning how failures propagate through system. Written using Macintosh Programmers Workshop C v3.1. Can be linked with CLIPS 5.0 (MSC-21927, available from COSMIC).

Investigating the soil removal characteristics of flexible tube coring method for lunar exploration

NASA Astrophysics Data System (ADS)

Tang, Junyue; Quan, Qiquan; Jiang, Shengyuan; Liang, Jieneng; Lu, Xiangyong; Yuan, Fengpei

2018-02-01

Compared with other technical solutions, sampling the planetary soil and returning it back to Earth may be the most direct method to seek the evidence of extraterrestrial life. To keep sample's stratification for further analyzing, a novel sampling method called flexible tube coring has been adopted for China future lunar explorations. Given the uncertain physical properties of lunar regolith, proper drilling parameters should be adjusted immediately in piercing process. Otherwise, only a small amount of core could be sampled and overload drilling faults could occur correspondingly. Due to the fact that the removed soil is inevitably connected with the cored soil, soil removal characteristics may have a great influence on both drilling loads and coring results. To comprehend the soil removal characteristics, a non-contact measurement was proposed and verified to acquire the coring and removal results accurately. Herein, further more experiments in one homogenous lunar regolith simulant were conducted, revealing that there exists a sudden core failure during the sampling process and the final coring results are determined by the penetration per revolution index. Due to the core failure, both drilling loads and soil's removal states are also affected thereby.

Therapy Insight: preserving fertility in cyclophosphamide-treated patients with rheumatic disease.

PubMed

Dooley, Mary Anne; Nair, Raj

2008-05-01

Cyclophosphamide remains a necessary treatment for severe rheumatic diseases, despite the continued search for alternative therapies with less gonadal toxicity. The risk of premature gonadal failure and sterility might lead young patients to delay treatment with cyclophosphamide. The patient's age at treatment and the cumulative dose received remain important risk factors for cyclophosphamide-induced gonadal failure in both males and females. Estrogen-containing oral contraceptives for females and testosterone for males are suggested to reduce the gonadal toxicity of cyclophosphamide, although few studies support these interventions. Owing to increased side effects, hormonal therapy is often avoided in patients with edema, hypertension, nephrotic syndrome or antiphospholipid antibodies. Agonists and antagonists of gonadotropin receptors are under study. Gonadotropin-receptor agonists might have beneficial effects in addition to suppression of sex-hormone production. The outcome of attempted cryopreservation of eggs, embryos or ovaries remains uncertain for women seeking to preserve their reproductive potential. Storing male gametes before chemotherapy is widely practiced and technically successful. As recovery of menses or production of testosterone does not predict individual fertility, identification of biomarkers of gonadal function and reserve, including serum levels of several hormones, ultrasonographic measurements of ovarian volume and antral follicle count, are necessary.

Predators of Greater Sage-Grouse nests identified by video monitoring

USGS Publications Warehouse

Coates, P.S.; Connelly, J.W.; Delehanty, D.J.

2008-01-01

Nest predation is the primary cause of nest failure for Greater Sage-Grouse (Centrocercus urophasianus), but the identity of their nest predators is often uncertain. Confirming the identity of these predators may be useful in enhancing management strategies designed to increase nest success. From 2002 to 2005, we monitored 87 Greater Sage-Grouse nests (camera, N = 55; no camera, N = 32) in northeastern Nevada and south-central Idaho and identified predators at 17 nests, with Common Ravens (Corvus corax) preying on eggs at 10 nests and American badgers (Taxidea taxis) at seven. Rodents were frequently observed at grouse nests, but did not prey on grouse eggs. Because sign left by ravens and badgers was often indistinguishable following nest predation, identifying nest predators based on egg removal, the presence of egg shells, or other sign was not possible. Most predation occurred when females were on nests. Active nest defense by grouse was rare and always unsuccessful. Continuous video monitoring of Sage-Grouse nests permitted unambiguous identification of nest predators. Additional monitoring studies could help improve our understanding of the causes of Sage-Grouse nest failure in the face of land-use changes in the Intermountain West. ?? 2008 Association of Field Ornithologists.

Sarcopenia, cachexia, and muscle performance in heart failure: Review update 2016.

PubMed

Saitoh, Masakazu; Ishida, Junichi; Doehner, Wolfram; von Haehling, Stephan; Anker, Markus S; Coats, Andrew J S; Anker, Stefan D; Springer, Jochen

2017-07-01

Cachexia in the context of heart failure (HF) has been termed cardiac cachexia, and represents a progressive involuntary weight loss. Cachexia is mainly the result of an imbalance in the homeostasis of muscle protein synthesis and degradation due to a lower activity of protein synthesis pathways and an over-activation of protein degradation. In addition, muscle wasting leads to of impaired functional capacity, even after adjusting for clinical relevant variables in patients with HF. However, there is no sufficient therapeutic strategy in muscle wasting in HF patients and very few studies in animal models. Exercise training represents a promising intervention that can prevent or even reverse the process of muscle wasting, and worsening the muscle function and performance in HF with muscle wasting and cachexia. The pathological mechanisms and effective therapeutic approach of cardiac cachexia remain uncertain, because of the difficulty to establish animal cardiac cachexia models, thus novel animal models are warranted. Furthermore, the use of improved animal models will lead to a better understanding of the pathways that modulate muscle wasting and therapeutics of muscle wasting of cardiac cachexia. Copyright © 2017 Elsevier B.V. All rights reserved.

The application of structural reliability techniques to plume impingement loading of the Space Station Freedom Photovoltaic Array

NASA Technical Reports Server (NTRS)

Yunis, Isam S.; Carney, Kelly S.

1993-01-01

A new aerospace application of structural reliability techniques is presented, where the applied forces depend on many probabilistic variables. This application is the plume impingement loading of the Space Station Freedom Photovoltaic Arrays. When the space shuttle berths with Space Station Freedom it must brake and maneuver towards the berthing point using its primary jets. The jet exhaust, or plume, may cause high loads on the photovoltaic arrays. The many parameters governing this problem are highly uncertain and random. An approach, using techniques from structural reliability, as opposed to the accepted deterministic methods, is presented which assesses the probability of failure of the array mast due to plume impingement loading. A Monte Carlo simulation of the berthing approach is used to determine the probability distribution of the loading. A probability distribution is also determined for the strength of the array. Structural reliability techniques are then used to assess the array mast design. These techniques are found to be superior to the standard deterministic dynamic transient analysis, for this class of problem. The results show that the probability of failure of the current array mast design, during its 15 year life, is minute.

Probabilistic Design of a Plate-Like Wing to Meet Flutter and Strength Requirements

NASA Technical Reports Server (NTRS)

Stroud, W. Jefferson; Krishnamurthy, T.; Mason, Brian H.; Smith, Steven A.; Naser, Ahmad S.

2002-01-01

An approach is presented for carrying out reliability-based design of a metallic, plate-like wing to meet strength and flutter requirements that are given in terms of risk/reliability. The design problem is to determine the thickness distribution such that wing weight is a minimum and the probability of failure is less than a specified value. Failure is assumed to occur if either the flutter speed is less than a specified allowable or the stress caused by a pressure loading is greater than a specified allowable. Four uncertain quantities are considered: wing thickness, calculated flutter speed, allowable stress, and magnitude of a uniform pressure load. The reliability-based design optimization approach described herein starts with a design obtained using conventional deterministic design optimization with margins on the allowables. Reliability is calculated using Monte Carlo simulation with response surfaces that provide values of stresses and flutter speed. During the reliability-based design optimization, the response surfaces and move limits are coordinated to ensure accuracy of the response surfaces. Studies carried out in the paper show the relationship between reliability and weight and indicate that, for the design problem considered, increases in reliability can be obtained with modest increases in weight.

Design and evaluation of a failure detection and isolation algorithm for restructurable control systems

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1986-01-01

The use of a decentralized approach to failure detection and isolation for use in restructurable control systems is examined. This work has produced: (1) A method for evaluating fundamental limits to FDI performance; (2) Application using flight recorded data; (3) A working control element FDI system with maximal sensitivity to critical control element failures; (4) Extensive testing on realistic simulations; and (5) A detailed design methodology involving parameter optimization (with respect to model uncertainties) and sensitivity analyses. This project has concentrated on detection and isolation of generic control element failures since these failures frequently lead to emergency conditions and since knowledge of remaining control authority is essential for control system redesign. The failures are generic in the sense that no temporal failure signature information was assumed. Thus, various forms of functional failures are treated in a unified fashion. Such a treatment results in a robust FDI system (i.e., one that covers all failure modes) but sacrifices some performance when detailed failure signature information is known, useful, and employed properly. It was assumed throughout that all sensors are validated (i.e., contain only in-spec errors) and that only the first failure of a single control element needs to be detected and isolated. The FDI system which has been developed will handle a class of multiple failures.

Failure detection system risk reduction assessment

NASA Technical Reports Server (NTRS)

Aguilar, Robert B. (Inventor); Huang, Zhaofeng (Inventor)

2012-01-01

A process includes determining a probability of a failure mode of a system being analyzed reaching a failure limit as a function of time to failure limit, determining a probability of a mitigation of the failure mode as a function of a time to failure limit, and quantifying a risk reduction based on the probability of the failure mode reaching the failure limit and the probability of the mitigation.

An Adaptive Control Technology for Safety of a GTM-like Aircraft

NASA Technical Reports Server (NTRS)

Matsutani, Megumi; Crespo, Luis G.; Annaswamy, Anuradha; Jang, Jinho

2010-01-01

An adaptive control architecture for safe performance of a transport aircraft subject to various adverse conditions is proposed and verified in this report. This architecture combines a nominal controller based on a Linear Quadratic Regulator with integral action, and an adaptive controller that accommodates actuator saturation and bounded disturbances. The effectiveness of the baseline controller and its adaptive augmentation are evaluated using a stand-alone control veri fication methodology. Case studies that pair individual parameter uncertainties with critical flight maneuvers are studied. The resilience of the controllers is determined by evaluating the degradation in closed-loop performance resulting from increasingly larger deviations in the uncertain parameters from their nominal values. Symmetric and asymmetric actuator failures, flight upsets, and center of gravity displacements, are some of the uncertainties considered.

A Comprehensive Investigation of Copper Pitting Corrosion in a Drinking Water Distribution System

EPA Science Inventory

Copper pipe pitting is a complicated corrosion process for which exact causes and solutions are uncertain. This paper presents the findings of a comprehensive investigation of a cold water copper pitting corrosion problem in a drinking water distribution system, including a refi...

Coping with Uncertainty in an Agile Systems Development Course

ERIC Educational Resources Information Center

Taipalus, Toni; Seppänen, Ville; Pirhonen, Maritta

2018-01-01

Uncertain and ambiguous environments are commonplace in information systems development (ISD) projects, and while different Agile frameworks welcome changes in organizational, technical, and business environments, the incurred uncertainty is known to negatively affect the development process and the quality of the final product. The effects of…

Shikonin ameliorates isoproterenol (ISO)-induced myocardial damage through suppressing fibrosis, inflammation, apoptosis and ER stress.

PubMed

Yang, Jun; Wang, Zhao; Chen, Dong-Lin

2017-09-01

Shikonin, isolated from the roots of herbal plant Lithospermum erythrorhizon, is a naphthoquinone. It has been reported to exert beneficial anti-inflammatory effects and anti-oxidant properties in various diseases. Isoproterenol (ISO) has been widely used to establish cardiac injury in vivo and in vitro. However, shikonin function in ISO-induced cardiac injury remains uncertain. In our study, we attempted to investigate the efficiency and possible molecular mechanism of shikonin in cardiac injury treatment induced by ISO. In vivo, C57BL6 mice were subcutaneously injected with 5mg/kg ISO to induce heart failure. And mice were given a gavage of shikonin (2 or 4mg/kg/d, for four weeks). Cardiac function, fibrosis indices, inflammation response, apoptosis and endoplasmic reticulum (ER) stress were calculated. Pathological alterations, fibrosis-, inflammation-, apoptosis- and ER stress-related molecules were examined. In ISO-induced cardiac injury, shikonin significantly ameliorated heart function, decreased myocardial fibrosis, suppressed inflammation, attenuated apoptosis and ER stress through impeding collagen accumulation, Toll like receptor 4/nuclear transcription factor κB (TLR4/NF-κB), Caspase-3 and glucose-regulated protein 78 (GRP78) signaling pathways activity, relieving heart failure in vivo. Also, in vitro, shikonin attenuated ISO-induced cardiac muscle cells by reducing fibrosis, inflammation, apoptosis and ER stress. Our findings indicated that shikonin treatment attenuated ISO-induced heart injury, providing an effective therapeutic strategy for heart failure treatment for future. Copyright © 2017. Published by Elsevier Masson SAS.

Biomechanical Comparison of Single- Versus Double-Row Capsulolabral Repair for Shoulder Instability: A Review.

PubMed

Yousif, Matthew John; Bicos, James

2017-12-01

The glenohumeral joint is the most commonly dislocated joint in the body. Failure rates of capsulolabral repair have been reported to be approximately 8%. Recent focus has been on restoration of the capsulolabral complex by a double-row capsulolabral repair technique in an effort to decrease redislocation rates after arthroscopic capsulolabral repair. To present a review of the biomechanical literature comparing single- versus double-row capsulolabral repairs and discuss the previous case series of double-row fixation. Narrative review. A simple review of the literature was performed by PubMed search. Only biomechanical studies comparing single- versus double-row capsulolabral repair were included for review. Only those case series and descriptive techniques with clinical results for double-row repair were included in the discussion. Biomechanical comparisons evaluating the native footprint of the labrum demonstrated significantly superior restoration of the footprint through double-row capsulolabral repair compared with single-row repair. Biomechanical comparisons of contact pressure at the repair interface, fracture displacement in bony Bankart lesion, load to failure, and decreased external rotation (suggestive of increased load to failure) were also significantly in favor of double- versus single-row repair. Recent descriptive techniques and case series of double-row fixation have demonstrated good clinical outcomes; however, no comparative clinical studies between single- and double-row repair have assessed functional outcomes. The superiority of double-row capsulolabral repair versus single-row repair remains uncertain because comparative studies assessing clinical outcomes have yet to be performed.

Multiple System Atrophy: An Oligodendroglioneural Synucleinopathy1

PubMed Central

Jellinger, Kurt A.

2017-01-01

Multiple system atrophy (MSA) is an orphan, fatal, adult-onset neurodegenerative disorder of uncertain etiology that is clinically characterized by various combinations of parkinsonism, cerebellar, autonomic, and motor dysfunction. MSA is an α-synucleinopathy with specific glioneuronal degeneration involving striatonigral, olivopontocerebellar, and autonomic nervous systems but also other parts of the central and peripheral nervous systems. The major clinical variants correlate with the morphologic phenotypes of striatonigral degeneration (MSA-P) and olivopontocerebellar atrophy (MSA-C). While our knowledge of the molecular pathogenesis of this devastating disease is still incomplete, updated consensus criteria and combined fluid and imaging biomarkers have increased its diagnostic accuracy. The neuropathologic hallmark of this unique proteinopathy is the deposition of aberrant α-synuclein in both glia (mainly oligodendroglia) and neurons forming glial and neuronal cytoplasmic inclusions that cause cell dysfunction and demise. In addition, there is widespread demyelination, the pathogenesis of which is not fully understood. The pathogenesis of MSA is characterized by propagation of misfolded α-synuclein from neurons to oligodendroglia and cell-to-cell spreading in a “prion-like” manner, oxidative stress, proteasomal and mitochondrial dysfunction, dysregulation of myelin lipids, decreased neurotrophic factors, neuroinflammation, and energy failure. The combination of these mechanisms finally results in a system-specific pattern of neurodegeneration and a multisystem involvement that are specific for MSA. Despite several pharmacological approaches in MSA models, addressing these pathogenic mechanisms, no effective neuroprotective nor disease-modifying therapeutic strategies are currently available. Multidisciplinary research to elucidate the genetic and molecular background of the deleterious cycle of noxious processes, to develop reliable biomarkers and targets for effective treatment of this hitherto incurable disorder is urgently needed. PMID:28984582

An uncertainty analysis of the hydrogen source term for a station blackout accident in Sequoyah using MELCOR 1.8.5

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

Gauntt, Randall O.; Bixler, Nathan E.; Wagner, Kenneth Charles

2014-03-01

A methodology for using the MELCOR code with the Latin Hypercube Sampling method was developed to estimate uncertainty in various predicted quantities such as hydrogen generation or release of fission products under severe accident conditions. In this case, the emphasis was on estimating the range of hydrogen sources in station blackout conditions in the Sequoyah Ice Condenser plant, taking into account uncertainties in the modeled physics known to affect hydrogen generation. The method uses user-specified likelihood distributions for uncertain model parameters, which may include uncertainties of a stochastic nature, to produce a collection of code calculations, or realizations, characterizing themore » range of possible outcomes. Forty MELCOR code realizations of Sequoyah were conducted that included 10 uncertain parameters, producing a range of in-vessel hydrogen quantities. The range of total hydrogen produced was approximately 583kg 131kg. Sensitivity analyses revealed expected trends with respected to the parameters of greatest importance, however, considerable scatter in results when plotted against any of the uncertain parameters was observed, with no parameter manifesting dominant effects on hydrogen generation. It is concluded that, with respect to the physics parameters investigated, in order to further reduce predicted hydrogen uncertainty, it would be necessary to reduce all physics parameter uncertainties similarly, bearing in mind that some parameters are inherently uncertain within a range. It is suspected that some residual uncertainty associated with modeling complex, coupled and synergistic phenomena, is an inherent aspect of complex systems and cannot be reduced to point value estimates. The probabilistic analyses such as the one demonstrated in this work are important to properly characterize response of complex systems such as severe accident progression in nuclear power plants.« less

Does intolerance of uncertainty predict anticipatory startle responses to uncertain threat?

PubMed

Nelson, Brady D; Shankman, Stewart A

2011-08-01

Intolerance of uncertainty (IU) has been proposed to be an important maintaining factor in several anxiety disorders, including generalized anxiety disorder, obsessive-compulsive disorder, and social phobia. While IU has been shown to predict subjective ratings and decision-making during uncertain/ambiguous situations, few studies have examined whether IU also predicts emotional responding to uncertain threat. The present study examined whether IU predicted aversive responding (startle and subjective ratings) during the anticipation of temporally uncertain shocks. Sixty-nine participants completed three experimental conditions during which they received: no shocks, temporally certain/predictable shocks, and temporally uncertain shocks. Results indicated that IU was negatively associated with startle during the uncertain threat condition in that those with higher IU had a smaller startle response. IU was also only related to startle during the uncertain (and not the certain/predictable) threat condition, suggesting that it was not predictive of general aversive responding, but specific to responses to uncertain aversiveness. Perceived control over anxiety-related events mediated the relation between IU and startle to uncertain threat, such that high IU led to lowered perceived control, which in turn led to a smaller startle response. We discuss several potential explanations for these findings, including the inhibitory qualities of IU. Overall, our results suggest that IU is associated with attenuated aversive responding to uncertain threat. Copyright © 2011 Elsevier B.V. All rights reserved.

The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.

PubMed

Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin

2018-04-05

This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.

Adapting environmental management to uncertain but inevitable change.

PubMed

Nicol, Sam; Fuller, Richard A; Iwamura, Takuya; Chadès, Iadine

2015-06-07

Implementation of adaptation actions to protect biodiversity is limited by uncertainty about the future. One reason for this is the fear of making the wrong decisions caused by the myriad future scenarios presented to decision-makers. We propose an adaptive management (AM) method for optimally managing a population under uncertain and changing habitat conditions. Our approach incorporates multiple future scenarios and continually learns the best management strategy from observations, even as conditions change. We demonstrate the performance of our AM approach by applying it to the spatial management of migratory shorebird habitats on the East Asian-Australasian flyway, predicted to be severely impacted by future sea-level rise. By accounting for non-stationary dynamics, our solution protects 25,000 more birds per year than the current best stationary approach. Our approach can be applied to many ecological systems that require efficient adaptation strategies for an uncertain future. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Expected value analysis for integrated supplier selection and inventory control of multi-product inventory system with fuzzy cost

NASA Astrophysics Data System (ADS)

Sutrisno, Widowati, Tjahjana, R. Heru

2017-12-01

The future cost in many industrial problem is obviously uncertain. Then a mathematical analysis for a problem with uncertain cost is needed. In this article, we deals with the fuzzy expected value analysis to solve an integrated supplier selection and supplier selection problem with uncertain cost where the costs uncertainty is approached by a fuzzy variable. We formulate the mathematical model of the problems fuzzy expected value based quadratic optimization with total cost objective function and solve it by using expected value based fuzzy programming. From the numerical examples result performed by the authors, the supplier selection problem was solved i.e. the optimal supplier was selected for each time period where the optimal product volume of all product that should be purchased from each supplier for each time period was determined and the product stock level was controlled as decided by the authors i.e. it was followed the given reference level.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reliability Analysis of Systems Subject to First-Passage Failure

NASA Technical Reports Server (NTRS)

Lutes, Loren D.; Sarkani, Shahram

2009-01-01

An obvious goal of reliability analysis is the avoidance of system failure. However, it is generally recognized that it is often not feasible to design a practical or useful system for which failure is impossible. Thus it is necessary to use techniques that estimate the likelihood of failure based on modeling the uncertainty about such items as the demands on and capacities of various elements in the system. This usually involves the use of probability theory, and a design is considered acceptable if it has a sufficiently small probability of failure. This report contains findings of analyses of systems subject to first-passage failure.

Variation in Dialysis Exposure Prior to Nonpreemptive Living Donor Kidney Transplantation in the United States and Its Association With Allograft Outcomes.

PubMed

Gill, John S; Rose, Caren; Joffres, Yayuk; Landsberg, David; Gill, Jagbir

2018-05-01

The impact of dialysis exposure before nonpreemptive living donor kidney transplantation on allograft outcomes is uncertain. Retrospective cohort study. Adult first-time recipients of kidney-only living donor transplants in the United States who were recorded within the Scientific Registry of Transplant Recipients for 2000 to 2016. Duration of pretransplantation dialysis exposure. Kidney transplant failure from any cause including death, death-censored transplant failure, and death with allograft function. Among the 77,607 living donor transplant recipients studied, longer pretransplantation dialysis exposure was independently associated with progressively higher risk for transplant failure from any cause, including death beginning 6 months after transplantation. Compared with patients with 0.1 to 3.0 months of dialysis exposure, the HR for transplant failure from any cause including death increased from 1.16 (95% CI, 1.07-1.31) among patients with 6.1 to 9.0 months of dialysis exposure to 1.60 (95% CI, 1.43-1.79) among patients with more than 60.0 months of dialysis exposure. Pretransplantation dialysis exposure varied markedly among centers; median exposures were 11.0 and 18.9 months for centers in the 10th and 90th percentiles of dialysis exposure, respectively. Centers with the highest proportions of living donor transplantations had the shortest pretransplantation dialysis exposures. In multivariable analysis, patients of black race, with low income, with nonprivate insurance, with less than high school education, and not working for income had longer pretransplantation dialysis exposures. Dialysis exposure in patients with these characteristics also varied 2-fold between transplantation centers. Why longer dialysis exposure is associated with transplant failure could not be determined. Longer pretransplantation dialysis exposure in nonpreemptive living donor kidney transplantation is associated with increased risk for allograft failure. Pretransplantation dialysis exposure is associated with recipients' sociodemographic and transplantation centers' characteristics. Understanding whether limiting pretransplantation dialysis exposure could improve living donor transplant outcomes will require further study. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Efficacy of β blockers in patients with heart failure plus atrial fibrillation: an individual-patient data meta-analysis.

PubMed

Kotecha, Dipak; Holmes, Jane; Krum, Henry; Altman, Douglas G; Manzano, Luis; Cleland, John G F; Lip, Gregory Y H; Coats, Andrew J S; Andersson, Bert; Kirchhof, Paulus; von Lueder, Thomas G; Wedel, Hans; Rosano, Giuseppe; Shibata, Marcelo C; Rigby, Alan; Flather, Marcus D

2014-12-20

Atrial fibrillation and heart failure often coexist, causing substantial cardiovascular morbidity and mortality. β blockers are indicated in patients with symptomatic heart failure with reduced ejection fraction; however, the efficacy of these drugs in patients with concomitant atrial fibrillation is uncertain. We therefore meta-analysed individual-patient data to assess the efficacy of β blockers in patients with heart failure and sinus rhythm compared with atrial fibrillation. We extracted individual-patient data from ten randomised controlled trials of the comparison of β blockers versus placebo in heart failure. The presence of sinus rhythm or atrial fibrillation was ascertained from the baseline electrocardiograph. The primary outcome was all-cause mortality. Analysis was by intention to treat. Outcome data were meta-analysed with an adjusted Cox proportional hazards regression. The study is registered with Clinicaltrials.gov, number NCT0083244, and PROSPERO, number CRD42014010012. 18,254 patients were assessed, and of these 13,946 (76%) had sinus rhythm and 3066 (17%) had atrial fibrillation at baseline. Crude death rates over a mean follow-up of 1·5 years (SD 1·1) were 16% (2237 of 13,945) in patients with sinus rhythm and 21% (633 of 3064) in patients with atrial fibrillation. β-blocker therapy led to a significant reduction in all-cause mortality in patients with sinus rhythm (hazard ratio 0·73, 0·67-0·80; p<0·001), but not in patients with atrial fibrillation (0·97, 0·83-1·14; p=0·73), with a significant p value for interaction of baseline rhythm (p=0·002). The lack of efficacy for the primary outcome was noted in all subgroups of atrial fibrillation, including age, sex, left ventricular ejection fraction, New York Heart Association class, heart rate, and baseline medical therapy. Based on our findings, β blockers should not be used preferentially over other rate-control medications and not regarded as standard therapy to improve prognosis in patients with concomitant heart failure and atrial fibrillation. Menarini Farmaceutica Internazionale (administrative support grant). Copyright © 2014 Elsevier Ltd. All rights reserved.

Cerulean Warbler Occurrence Atlas for Military Installations

DTIC Science & Technology

2010-04-01

Army Ammuniton Plant (Closed) IN NO 2009 Army IOWA ARMY AMMUNITION PLANT IA UNCERTAIN 2009 USACE J. Percy Priest Lake TN UNCERTAIN 2009 USACE J...Stonewall Jackson Lake WV UNCERTAIN 2009 USACE Summersville Lake WV no POC Army Sunflower Army Ammunition Plant KS no POC USACE Sutton Lake WV UNCERTAIN

Sensor Data Fusion with Z-Numbers and Its Application in Fault Diagnosis

PubMed Central

Jiang, Wen; Xie, Chunhe; Zhuang, Miaoyan; Shou, Yehang; Tang, Yongchuan

2016-01-01

Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-number, Z = (A, B), can represent the fuzziness and the reliability of information simultaneously, where the first component A represents a fuzzy restriction on the values of uncertain variables and the second component B is a measure of the reliability of A. In order to model and process the uncertainties in a sensor data fusion system reasonably, in this paper, a novel method combining the Z-number and Dempster–Shafer (D-S) evidence theory is proposed, where the Z-number is used to model the fuzziness and reliability of the sensor data and the D-S evidence theory is used to fuse the uncertain information of Z-numbers. The main advantages of the proposed method are that it provides a more robust measure of reliability to the sensor data, and the complementary information of multi-sensors reduces the uncertainty of the fault recognition, thus enhancing the reliability of fault detection. PMID:27649193

Resolving structural uncertainty in natural resources management using POMDP approaches

USGS Publications Warehouse

Williams, B.K.

2011-01-01

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems. ?? 2011.

Robust Unit Commitment Considering Uncertain Demand Response

DOE PAGES

Liu, Guodong; Tomsovic, Kevin

2014-09-28

Although price responsive demand response has been widely accepted as playing an important role in the reliable and economic operation of power system, the real response from demand side can be highly uncertain due to limited understanding of consumers' response to pricing signals. To model the behavior of consumers, the price elasticity of demand has been explored and utilized in both research and real practice. However, the price elasticity of demand is not precisely known and may vary greatly with operating conditions and types of customers. To accommodate the uncertainty of demand response, alternative unit commitment methods robust to themore » uncertainty of the demand response require investigation. In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand. By optimizing the worst case under proper robust level, the unit commitment solution of the proposed model is robust against all possible realizations of the modeled uncertain demand response. Numerical simulations on the IEEE Reliability Test System show the e ectiveness of the method. Finally, compared to unit commitment with deterministic price elasticity of demand, the proposed robust model can reduce the average Locational Marginal Prices (LMPs) as well as the price volatility.« less

A Hierarchical Multi-Model Approach for Uncertainty Segregation, Prioritization and Comparative Evaluation of Competing Modeling Propositions

NASA Astrophysics Data System (ADS)

Tsai, F. T.; Elshall, A. S.; Hanor, J. S.

2012-12-01

Subsurface modeling is challenging because of many possible competing propositions for each uncertain model component. How can we judge that we are selecting the correct proposition for an uncertain model component out of numerous competing propositions? How can we bridge the gap between synthetic mental principles such as mathematical expressions on one hand, and empirical observation such as observation data on the other hand when uncertainty exists on both sides? In this study, we introduce hierarchical Bayesian model averaging (HBMA) as a multi-model (multi-proposition) framework to represent our current state of knowledge and decision for hydrogeological structure modeling. The HBMA framework allows for segregating and prioritizing different sources of uncertainty, and for comparative evaluation of competing propositions for each source of uncertainty. We applied the HBMA to a study of hydrostratigraphy and uncertainty propagation of the Southern Hills aquifer system in the Baton Rouge area, Louisiana. We used geophysical data for hydrogeological structure construction through indictor hydrostratigraphy method and used lithologic data from drillers' logs for model structure calibration. However, due to uncertainty in model data, structure and parameters, multiple possible hydrostratigraphic models were produced and calibrated. The study considered four sources of uncertainties. To evaluate mathematical structure uncertainty, the study considered three different variogram models and two geological stationarity assumptions. With respect to geological structure uncertainty, the study considered two geological structures with respect to the Denham Springs-Scotlandville fault. With respect to data uncertainty, the study considered two calibration data sets. These four sources of uncertainty with their corresponding competing modeling propositions resulted in 24 calibrated models. The results showed that by segregating different sources of uncertainty, HBMA analysis provided insights on uncertainty priorities and propagation. In addition, it assisted in evaluating the relative importance of competing modeling propositions for each uncertain model component. By being able to dissect the uncertain model components and provide weighted representation of the competing propositions for each uncertain model component based on the background knowledge, the HBMA functions as an epistemic framework for advancing knowledge about the system under study.

Forecasting overhaul or replacement intervals based on estimated system failure intensity

NASA Astrophysics Data System (ADS)

Gannon, James M.

1994-12-01

System reliability can be expressed in terms of the pattern of failure events over time. Assuming a nonhomogeneous Poisson process and Weibull intensity function for complex repairable system failures, the degree of system deterioration can be approximated. Maximum likelihood estimators (MLE's) for the system Rate of Occurrence of Failure (ROCOF) function are presented. Evaluating the integral of the ROCOF over annual usage intervals yields the expected number of annual system failures. By associating a cost of failure with the expected number of failures, budget and program policy decisions can be made based on expected future maintenance costs. Monte Carlo simulation is used to estimate the range and the distribution of the net present value and internal rate of return of alternative cash flows based on the distributions of the cost inputs and confidence intervals of the MLE's.

Distributed Fault-Tolerant Control of Networked Uncertain Euler-Lagrange Systems Under Actuator Faults.

PubMed

Chen, Gang; Song, Yongduan; Lewis, Frank L

2016-05-03

This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.

A global analysis approach for investigating structural resilience in urban drainage systems.

PubMed

Mugume, Seith N; Gomez, Diego E; Fu, Guangtao; Farmani, Raziyeh; Butler, David

2015-09-15

Building resilience in urban drainage systems requires consideration of a wide range of threats that contribute to urban flooding. Existing hydraulic reliability based approaches have focused on quantifying functional failure caused by extreme rainfall or increase in dry weather flows that lead to hydraulic overloading of the system. Such approaches however, do not fully explore the full system failure scenario space due to exclusion of crucial threats such as equipment malfunction, pipe collapse and blockage that can also lead to urban flooding. In this research, a new analytical approach based on global resilience analysis is investigated and applied to systematically evaluate the performance of an urban drainage system when subjected to a wide range of structural failure scenarios resulting from random cumulative link failure. Link failure envelopes, which represent the resulting loss of system functionality (impacts) are determined by computing the upper and lower limits of the simulation results for total flood volume (failure magnitude) and average flood duration (failure duration) at each link failure level. A new resilience index that combines the failure magnitude and duration into a single metric is applied to quantify system residual functionality at each considered link failure level. With this approach, resilience has been tested and characterised for an existing urban drainage system in Kampala city, Uganda. In addition, the effectiveness of potential adaptation strategies in enhancing its resilience to cumulative link failure has been tested. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Developing a Software for Fuzzy Group Decision Support System: A Case Study

ERIC Educational Resources Information Center

Baba, A. Fevzi; Kuscu, Dincer; Han, Kerem

2009-01-01

The complex nature and uncertain information in social problems required the emergence of fuzzy decision support systems in social areas. In this paper, we developed user-friendly Fuzzy Group Decision Support Systems (FGDSS) software. The software can be used for multi-purpose decision making processes. It helps the users determine the main and…

The Role of Central Nervous System Plasticity in Tinnitus

ERIC Educational Resources Information Center

Saunders, James C.

2007-01-01

Tinnitus is a vexing disorder of hearing characterized by sound sensations originating in the head without any external stimulation. The specific etiology of these sensations is uncertain but frequently associated with hearing loss. The "neurophysiogical" model of tinnitus has enhanced appreciation of central nervous system (CNS) contributions.…

Application of the Auto-Tuned Land Assimilation System (ATLAS) to ASCAT and SMOS soil moisture retrieval products

USDA-ARS?s Scientific Manuscript database

Land data assimilations are typically based on highly uncertain assumptions regarding the statistical structure of observation and modeling errors. Left uncorrected, poor assumptions can degrade the quality of analysis products generated by land data assimilation systems. Recently, Crow and van de...

National airspace system : FAA reauthorization issues are critical to system transformation and operations statement of Gerald L. Dillingham, Ph.D.

DOT National Transportation Integrated Search

2009-02-01

As requested, this statement discusses issues for the reauthorization of the Federal Aviation Administration (FAA). The aviation industry is in a period of economic turmoil and faces an : uncertain future. At the same time, FAA is undertaking one of ...

Reliability analysis based on the losses from failures.

PubMed

Todinov, M T

2006-04-01

The conventional reliability analysis is based on the premise that increasing the reliability of a system will decrease the losses from failures. On the basis of counterexamples, it is demonstrated that this is valid only if all failures are associated with the same losses. In case of failures associated with different losses, a system with larger reliability is not necessarily characterized by smaller losses from failures. Consequently, a theoretical framework and models are proposed for a reliability analysis, linking reliability and the losses from failures. Equations related to the distributions of the potential losses from failure have been derived. It is argued that the classical risk equation only estimates the average value of the potential losses from failure and does not provide insight into the variability associated with the potential losses. Equations have also been derived for determining the potential and the expected losses from failures for nonrepairable and repairable systems with components arranged in series, with arbitrary life distributions. The equations are also valid for systems/components with multiple mutually exclusive failure modes. The expected losses given failure is a linear combination of the expected losses from failure associated with the separate failure modes scaled by the conditional probabilities with which the failure modes initiate failure. On this basis, an efficient method for simplifying complex reliability block diagrams has been developed. Branches of components arranged in series whose failures are mutually exclusive can be reduced to single components with equivalent hazard rate, downtime, and expected costs associated with intervention and repair. A model for estimating the expected losses from early-life failures has also been developed. For a specified time interval, the expected losses from early-life failures are a sum of the products of the expected number of failures in the specified time intervals covering the early-life failures region and the expected losses given failure characterizing the corresponding time intervals. For complex systems whose components are not logically arranged in series, discrete simulation algorithms and software have been created for determining the losses from failures in terms of expected lost production time, cost of intervention, and cost of replacement. Different system topologies are assessed to determine the effect of modifications of the system topology on the expected losses from failures. It is argued that the reliability allocation in a production system should be done to maximize the profit/value associated with the system. Consequently, a method for setting reliability requirements and reliability allocation maximizing the profit by minimizing the total cost has been developed. Reliability allocation that maximizes the profit in case of a system consisting of blocks arranged in series is achieved by determining for each block individually the reliabilities of the components in the block that minimize the sum of the capital, operation costs, and the expected losses from failures. A Monte Carlo simulation based net present value (NPV) cash-flow model has also been proposed, which has significant advantages to cash-flow models based on the expected value of the losses from failures per time interval. Unlike these models, the proposed model has the capability to reveal the variation of the NPV due to different number of failures occurring during a specified time interval (e.g., during one year). The model also permits tracking the impact of the distribution pattern of failure occurrences and the time dependence of the losses from failures.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations

PubMed Central

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

PubMed

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

DEPEND - A design environment for prediction and evaluation of system dependability

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.; Iyer, Ravishankar K.

1990-01-01

The development of DEPEND, an integrated simulation environment for the design and dependability analysis of fault-tolerant systems, is described. DEPEND models both hardware and software components at a functional level, and allows automatic failure injection to assess system performance and reliability. It relieves the user of the work needed to inject failures, maintain statistics, and output reports. The automatic failure injection scheme is geared toward evaluating a system under high stress (workload) conditions. The failures that are injected can affect both hardware and software components. To illustrate the capability of the simulator, a distributed system which employs a prediction-based, dynamic load-balancing heuristic is evaluated. Experiments were conducted to determine the impact of failures on system performance and to identify the failures to which the system is especially susceptible.

49 CFR 214.529 - In-service failure of primary braking system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false In-service failure of primary braking system. 214... Maintenance Machines and Hi-Rail Vehicles § 214.529 In-service failure of primary braking system. (a) In the event of a total in-service failure of its primary braking system, an on-track roadway maintenance...

49 CFR 214.529 - In-service failure of primary braking system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false In-service failure of primary braking system. 214... Maintenance Machines and Hi-Rail Vehicles § 214.529 In-service failure of primary braking system. (a) In the event of a total in-service failure of its primary braking system, an on-track roadway maintenance...

49 CFR 214.529 - In-service failure of primary braking system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Maintenance Machines and Hi-Rail Vehicles § 214.529 In-service failure of primary braking system. (a) In the event of a total in-service failure of its primary braking system, an on-track roadway maintenance... 49 Transportation 4 2010-10-01 2010-10-01 false In-service failure of primary braking system. 214...

Studies in knowledge-based diagnosis of failures in robotic assembly

NASA Technical Reports Server (NTRS)

Lam, Raymond K.; Pollard, Nancy S.; Desai, Rajiv S.

1990-01-01

The telerobot diagnostic system (TDS) is a knowledge-based system that is being developed for identification and diagnosis of failures in the space robotic domain. The system is able to isolate the symptoms of the failure, generate failure hypotheses based on these symptoms, and test their validity at various levels by interpreting or simulating the effects of the hypotheses on results of plan execution. The implementation of the TDS is outlined. The classification of failures and the types of system models used by the TDS are discussed. A detailed example of the TDS approach to failure diagnosis is provided.

Uncertainty quantification tools for multiphase gas-solid flow simulations using MFIX

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

Fox, Rodney O.; Passalacqua, Alberto

2016-02-01

Computational fluid dynamics (CFD) has been widely studied and used in the scientific community and in the industry. Various models were proposed to solve problems in different areas. However, all models deviate from reality. Uncertainty quantification (UQ) process evaluates the overall uncertainties associated with the prediction of quantities of interest. In particular it studies the propagation of input uncertainties to the outputs of the models so that confidence intervals can be provided for the simulation results. In the present work, a non-intrusive quadrature-based uncertainty quantification (QBUQ) approach is proposed. The probability distribution function (PDF) of the system response can bemore » then reconstructed using extended quadrature method of moments (EQMOM) and extended conditional quadrature method of moments (ECQMOM). The report first explains the theory of QBUQ approach, including methods to generate samples for problems with single or multiple uncertain input parameters, low order statistics, and required number of samples. Then methods for univariate PDF reconstruction (EQMOM) and multivariate PDF reconstruction (ECQMOM) are explained. The implementation of QBUQ approach into the open-source CFD code MFIX is discussed next. At last, QBUQ approach is demonstrated in several applications. The method is first applied to two examples: a developing flow in a channel with uncertain viscosity, and an oblique shock problem with uncertain upstream Mach number. The error in the prediction of the moment response is studied as a function of the number of samples, and the accuracy of the moments required to reconstruct the PDF of the system response is discussed. The QBUQ approach is then demonstrated by considering a bubbling fluidized bed as example application. The mean particle size is assumed to be the uncertain input parameter. The system is simulated with a standard two-fluid model with kinetic theory closures for the particulate phase implemented into MFIX. The effect of uncertainty on the disperse-phase volume fraction, on the phase velocities and on the pressure drop inside the fluidized bed are examined, and the reconstructed PDFs are provided for the three quantities studied. Then the approach is applied to a bubbling fluidized bed with two uncertain parameters, particle-particle and particle-wall restitution coefficients. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities and gas pressure are provided. The PDFs of the response are reconstructed using EQMOM with appropriate kernel density functions. The simulation results are compared to experimental data provided by the 2013 NETL small-scale challenge problem. Lastly, the proposed procedure is demonstrated by considering a riser of a circulating fluidized bed as an example application. The mean particle size is considered to be the uncertain input parameter. Contour plots of the mean and standard deviation of solid volume fraction, solid phase velocities, and granular temperature are provided. Mean values and confidence intervals of the quantities of interest are compared to the experiment results. The univariate and bivariate PDF reconstructions of the system response are performed using EQMOM and ECQMOM.« less

CRYOGENIC UPPER STAGE SYSTEM SAFETY

NASA Technical Reports Server (NTRS)

Smith, R. Kenneth; French, James V.; LaRue, Peter F.; Taylor, James L.; Pollard, Kathy (Technical Monitor)

2005-01-01

NASA s Exploration Initiative will require development of many new systems or systems of systems. One specific example is that safe, affordable, and reliable upper stage systems to place cargo and crew in stable low earth orbit are urgently required. In this paper, we examine the failure history of previous upper stages with liquid oxygen (LOX)/liquid hydrogen (LH2) propulsion systems. Launch data from 1964 until midyear 2005 are analyzed and presented. This data analysis covers upper stage systems from the Ariane, Centaur, H-IIA, Saturn, and Atlas in addition to other vehicles. Upper stage propulsion system elements have the highest impact on reliability. This paper discusses failure occurrence in all aspects of the operational phases (Le., initial burn, coast, restarts, and trends in failure rates over time). In an effort to understand the likelihood of future failures in flight, we present timelines of engine system failures relevant to initial flight histories. Some evidence suggests that propulsion system failures as a result of design problems occur shortly after initial development of the propulsion system; whereas failures because of manufacturing or assembly processing errors may occur during any phase of the system builds process, This paper also explores the detectability of historical failures. Observations from this review are used to ascertain the potential for increased upper stage reliability given investments in integrated system health management. Based on a clear understanding of the failure and success history of previous efforts by multiple space hardware development groups, the paper will investigate potential improvements that can be realized through application of system safety principles.

A review of wiring system safety in space power systems

NASA Technical Reports Server (NTRS)

Stavnes, Mark W.; Hammoud, Ahmad N.

1993-01-01

Wiring system failures have resulted from arc propagation in the wiring harnesses of current aerospace vehicles. These failures occur when the insulation becomes conductive upon the initiation of an arc. In some cases, the conductive path of the carbon arc track displays a high enough resistance such that the current is limited, and therefore may be difficult to detect using conventional circuit protection. Often, such wiring failures are not simply the result of insulation failure, but are due to a combination of wiring system factors. Inadequate circuit protection, unforgiving system designs, and careless maintenance procedures can contribute to a wiring system failure. This paper approaches the problem with respect to the overall wiring system, in order to determine what steps can be taken to improve the reliability, maintainability, and safety of space power systems. Power system technologies, system designs, and maintenance procedures which have led to past wiring system failures will be discussed. New technologies, design processes, and management techniques which may lead to improved wiring system safety will be introduced.

Decision Making Methodology to Mitigate Damage From Glacial Lake Outburst Floods From Imja Lake in Nepal

NASA Astrophysics Data System (ADS)

McKinney, D. C.; Cuellar, A. D.

2015-12-01

Climate change has accelerated glacial retreat in high altitude glaciated regions of Nepal leading to the growth and formation of glacier lakes. Glacial lake outburst floods (GLOF) are sudden events triggered by an earthquake, moraine failure or other shock that causes a sudden outflow of water. These floods are catastrophic because of their sudden onset, the difficulty predicting them, and enormous quantity of water and debris rapidly flooding downstream areas. Imja Lake in the Himalaya of Nepal has experienced accelerated growth since it first appeared in the 1960s. Communities threatened by a flood from Imja Lake have advocated for projects to adapt to the increasing threat of a GLOF. Nonetheless, discussions surrounding projects for Imja have not included a rigorous analysis of the potential consequences of a flood, probability of an event, or costs of mitigation projects in part because this information is unknown or uncertain. This work presents a demonstration of a decision making methodology developed to rationally analyze the risks posed by Imja Lake and the various adaptation projects proposed using available information. In this work the authors use decision analysis, data envelopement analysis (DEA), and sensitivity analysis to assess proposed adaptation measures that would mitigate damage in downstream communities from a GLOF. We use an existing hydrodynamic model of the at-risk area to determine how adaptation projects will affect downstream flooding and estimate fatalities using an empirical method developed for dam failures. The DEA methodology allows us to estimate the value of a statistical life implied by each project given the cost of the project and number of lives saved to determine which project is the most efficient. In contrast the decision analysis methodology requires fatalities to be assigned a cost but allows the inclusion of uncertainty in the decision making process. We compare the output of these two methodologies and determine the sensitivity of the conclusions to changes in uncertain input parameters including project cost, value of a statistical life, and time to a GLOF event.

Development of an adaptive failure detection and identification system for detecting aircraft control element failures

NASA Technical Reports Server (NTRS)

Bundick, W. Thomas

1990-01-01

A methodology for designing a failure detection and identification (FDI) system to detect and isolate control element failures in aircraft control systems is reviewed. An FDI system design for a modified B-737 aircraft resulting from this methodology is also reviewed, and the results of evaluating this system via simulation are presented. The FDI system performed well in a no-turbulence environment, but it experienced an unacceptable number of false alarms in atmospheric turbulence. An adaptive FDI system, which adjusts thresholds and other system parameters based on the estimated turbulence level, was developed and evaluated. The adaptive system performed well over all turbulence levels simulated, reliably detecting all but the smallest magnitude partially-missing-surface failures.

Uncertain dynamical systems: A differential game approach

NASA Technical Reports Server (NTRS)

Gutman, S.

1976-01-01

A class of dynamical systems in a conflict situation is formulated and discussed, and the formulation is applied to the study of an important class of systems in the presence of uncertainty. The uncertainty is deterministic and the only assumption is that its value belongs to a known compact set. Asymptotic stability is fully discussed with application to variable structure and model reference control systems.

Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

PubMed

Mazandarani, Mehran; Pariz, Naser

2018-05-01

This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty

NASA Astrophysics Data System (ADS)

Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design, thus alleviating the risk of mis-adaptation, namely the design of a solution fully adapted to a scenario that is different from the one that will actually realize.

Applied estimation for hybrid dynamical systems using perceptional information

NASA Astrophysics Data System (ADS)

Plotnik, Aaron M.

This dissertation uses the motivating example of robotic tracking of mobile deep ocean animals to present innovations in robotic perception and estimation for hybrid dynamical systems. An approach to estimation for hybrid systems is presented that utilizes uncertain perceptional information about the system's mode to improve tracking of its mode and continuous states. This results in significant improvements in situations where previously reported methods of estimation for hybrid systems perform poorly due to poor distinguishability of the modes. The specific application that motivates this research is an automatic underwater robotic observation system that follows and films individual deep ocean animals. A first version of such a system has been developed jointly by the Stanford Aerospace Robotics Laboratory and Monterey Bay Aquarium Research Institute (MBARI). This robotic observation system is successfully fielded on MBARI's ROVs, but agile specimens often evade the system. When a human ROV pilot performs this task, one advantage that he has over the robotic observation system in these situations is the ability to use visual perceptional information about the target, immediately recognizing any changes in the specimen's behavior mode. With the approach of the human pilot in mind, a new version of the robotic observation system is proposed which is extended to (a) derive perceptional information (visual cues) about the behavior mode of the tracked specimen, and (b) merge this dissimilar, discrete and uncertain information with more traditional continuous noisy sensor data by extending existing algorithms for hybrid estimation. These performance enhancements are enabled by integrating techniques in hybrid estimation, computer vision and machine learning. First, real-time computer vision and classification algorithms extract a visual observation of the target's behavior mode. Existing hybrid estimation algorithms are extended to admit this uncertain but discrete observation, complementing the information available from more traditional sensors. State tracking is achieved using a new form of Rao-Blackwellized particle filter called the mode-observed Gaussian Particle Filter. Performance is demonstrated using data from simulation and data collected on actual specimens in the ocean. The framework for estimation using both traditional and perceptional information is easily extensible to other stochastic hybrid systems with mode-related perceptional observations available.

A comparison of pay-as-bid and marginal pricing in electricity markets

NASA Astrophysics Data System (ADS)

Ren, Yongjun

This thesis investigates the behaviour of electricity markets under marginal and pay-as-bid pricing. Marginal pricing is believed to yield the maximum social welfare and is currently implemented by most electricity markets. However, in view of recent electricity market failures, pay-as-bid has been extensively discussed as a possible alternative to marginal pricing. In this research, marginal and pay-as-bid pricing have been analyzed in electricity markets with both perfect and imperfect competition. The perfect competition case is studied under both exact and uncertain system marginal cost prediction. The comparison of the two pricing methods is conducted through two steps: (i) identify the best offer strategy of the generating companies (gencos); (ii) analyze the market performance under these optimum genco strategies. The analysis results together with numerical simulations show that pay-as-bid and marginal pricing are equivalent in a perfect market with exact system marginal cost prediction. In perfect markets with uncertain demand prediction, the two pricing methods are also equivalent but in an expected value sense. If we compare from the perspective of second order statistics, all market performance measures exhibit much lower values under pay-as-bid than under marginal pricing. The risk of deviating from the mean is therefore much higher under marginal pricing than under pay-as-bid. In an imperfect competition market with exact demand prediction, the research shows that pay-as-bid pricing yields lower consumer payments and lower genco profits. This research provides quantitative evidence that challenges some common claims about pay-as-bid pricing. One is that under pay-as-bid, participants would soon learn how to offer so as to obtain the same or higher profits than what they would have obtained under marginal pricing. This research however shows that, under pay-as-bid, participants can at best earn the same profit or expected profit as under marginal pricing. A second common claim refuted by this research is that pay-as-bid does not provide correct price signals if there is a scarcity of generation resources. We show that pay-as-bid does provide a price signal with such characteristics and furthermore argue that the price signal under marginal pricing with gaming may not necessarily be correct since it would then not reflect a lack of generation capacity but a desire to increase profit.

Capacity planning for waste management systems: an interval fuzzy robust dynamic programming approach.

PubMed

Nie, Xianghui; Huang, Guo H; Li, Yongping

2009-11-01

This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information.

Interval type-2 fuzzy PID controller for uncertain nonlinear inverted pendulum system.

PubMed

El-Bardini, Mohammad; El-Nagar, Ahmad M

2014-05-01

In this paper, the interval type-2 fuzzy proportional-integral-derivative controller (IT2F-PID) is proposed for controlling an inverted pendulum on a cart system with an uncertain model. The proposed controller is designed using a new method of type-reduction that we have proposed, which is called the simplified type-reduction method. The proposed IT2F-PID controller is able to handle the effect of structure uncertainties due to the structure of the interval type-2 fuzzy logic system (IT2-FLS). The results of the proposed IT2F-PID controller using a new method of type-reduction are compared with the other proposed IT2F-PID controller using the uncertainty bound method and the type-1 fuzzy PID controller (T1F-PID). The simulation and practical results show that the performance of the proposed controller is significantly improved compared with the T1F-PID controller. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Uncertain dynamic analysis for rigid-flexible mechanisms with random geometry and material properties

NASA Astrophysics Data System (ADS)

Wu, Jinglai; Luo, Zhen; Zhang, Nong; Zhang, Yunqing; Walker, Paul D.

2017-02-01

This paper proposes an uncertain modelling and computational method to analyze dynamic responses of rigid-flexible multibody systems (or mechanisms) with random geometry and material properties. Firstly, the deterministic model for the rigid-flexible multibody system is built with the absolute node coordinate formula (ANCF), in which the flexible parts are modeled by using ANCF elements, while the rigid parts are described by ANCF reference nodes (ANCF-RNs). Secondly, uncertainty for the geometry of rigid parts is expressed as uniform random variables, while the uncertainty for the material properties of flexible parts is modeled as a continuous random field, which is further discretized to Gaussian random variables using a series expansion method. Finally, a non-intrusive numerical method is developed to solve the dynamic equations of systems involving both types of random variables, which systematically integrates the deterministic generalized-α solver with Latin Hypercube sampling (LHS) and Polynomial Chaos (PC) expansion. The benchmark slider-crank mechanism is used as a numerical example to demonstrate the characteristics of the proposed method.

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

What's wrong with hazard-ranking systems? An expository note.

PubMed

Cox, Louis Anthony Tony

2009-07-01

Two commonly recommended principles for allocating risk management resources to remediate uncertain hazards are: (1) select a subset to maximize risk-reduction benefits (e.g., maximize the von Neumann-Morgenstern expected utility of the selected risk-reducing activities), and (2) assign priorities to risk-reducing opportunities and then select activities from the top of the priority list down until no more can be afforded. When different activities create uncertain but correlated risk reductions, as is often the case in practice, then these principles are inconsistent: priority scoring and ranking fails to maximize risk-reduction benefits. Real-world risk priority scoring systems used in homeland security and terrorism risk assessment, environmental risk management, information system vulnerability rating, business risk matrices, and many other important applications do not exploit correlations among risk-reducing opportunities or optimally diversify risk-reducing investments. As a result, they generally make suboptimal risk management recommendations. Applying portfolio optimization methods instead of risk prioritization ranking, rating, or scoring methods can achieve greater risk-reduction value for resources spent.

Comprehension and retrieval of failure cases in airborne observatories

NASA Technical Reports Server (NTRS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-01-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

NASA Astrophysics Data System (ADS)

Zhang, Ying-Zhi; Liu, Jin-Tong; Shen, Gui-Xiang; Long, Zhe; Sun, Shu-Guang

2017-07-01

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

Comprehension and retrieval of failure cases in airborne observatories

NASA Astrophysics Data System (ADS)

Alvarado, Sergio J.; Mock, Kenrick J.

1995-05-01

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Ampoule Failure System

NASA Technical Reports Server (NTRS)

Watring, Dale A. (Inventor); Johnson, Martin L. (Inventor)

1996-01-01

An ampoule failure system for use in material processing furnaces comprising a containment cartridge and an ampoule failure sensor. The containment cartridge contains an ampoule of toxic material therein and is positioned within a furnace for processing. An ampoule failure probe is positioned in the containment cartridge adjacent the ampoule for detecting a potential harmful release of toxic material therefrom during processing. The failure probe is spaced a predetermined distance from the ampoule and is chemically chosen so as to undergo a timely chemical reaction with the toxic material upon the harmful release thereof. The ampoule failure system further comprises a data acquisition system which is positioned externally of the furnace and is electrically connected to the ampoule failure probe so as to form a communicating electrical circuit. The data acquisition system includes an automatic shutdown device for shutting down the furnace upon the harmful release of toxic material. It also includes a resistance measuring device for measuring the resistance of the failure probe during processing. The chemical reaction causes a step increase in resistance of the failure probe whereupon the automatic shutdown device will responsively shut down the furnace.

Simulating fail-stop in asynchronous distributed systems

NASA Technical Reports Server (NTRS)

Sabel, Laura; Marzullo, Keith

1994-01-01

The fail-stop failure model appears frequently in the distributed systems literature. However, in an asynchronous distributed system, the fail-stop model cannot be implemented. In particular, it is impossible to reliably detect crash failures in an asynchronous system. In this paper, we show that it is possible to specify and implement a failure model that is indistinguishable from the fail-stop model from the point of view of any process within an asynchronous system. We give necessary conditions for a failure model to be indistinguishable from the fail-stop model, and derive lower bounds on the amount of process replication needed to implement such a failure model. We present a simple one-round protocol for implementing one such failure model, which we call simulated fail-stop.

Toward a formal definition of water scarcity in natural human systems

Treesearch

W.K. Jaeger; A.J. Plantinga; H. Chang; K. Dello; G. Grant; D. Hulse; J.J. McDonnell; S. Lancaster; H. Moradkhani; A.T. Morzillo; P. Mote; A. Nolin; M. Santlemann; J. Wu

2013-01-01

Water scarcity may appear to be a simple concept, but it can be difficult to apply to complex natural-human systems. While aggregate scarcity indices are straightforward to compute, they do not adequately represent the spatial and temporal variations in water scarcity that arise from complex systems interactions. The uncertain effects of future climate change on water...

Load Modeling and Calibration Techniques for Power System Studies

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

Chassin, Forrest S.; Mayhorn, Ebony T.; Elizondo, Marcelo A.

2011-09-23

Load modeling is the most uncertain area in power system simulations. Having an accurate load model is important for power system planning and operation. Here, a review of load modeling and calibration techniques is given. This paper is not comprehensive, but covers some of the techniques most commonly found in the literature. The advantages and disadvantages of each technique are outlined.

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Aberrant activation of the human sex-determining gene in early embryonic development results in postnatal growth retardation and lethality in mice.

PubMed

Kido, Tatsuo; Sun, Zhaoyu; Lau, Yun-Fai Chris

2017-06-23

Sexual dimorphisms are prevalent in development, physiology and diseases in humans. Currently, the contributions of the genes on the male-specific region of the Y chromosome (MSY) in these processes are uncertain. Using a transgene activation system, the human sex-determining gene hSRY is activated in the single-cell embryos of the mouse. Pups with hSRY activated (hSRY ON ) are born of similar sizes as those of non-activated controls. However, they retard significantly in postnatal growth and development and all die of multi-organ failure before two weeks of age. Pathological and molecular analyses indicate that hSRY ON pups lack innate suckling activities, and develop fatty liver disease, arrested alveologenesis in the lung, impaired neurogenesis in the brain and occasional myocardial fibrosis and minimized thymus development. Transcriptome analysis shows that, in addition to those unique to the respective organs, various cell growth and survival pathways and functions are differentially affected in the transgenic mice. These observations suggest that ectopic activation of a Y-located SRY gene could exert male-specific effects in development and physiology of multiple organs, thereby contributing to sexual dimorphisms in normal biological functions and disease processes in affected individuals.

Weight of evidence evaluation of a network of adverse ...

EPA Pesticide Factsheets

Ongoing honey bee colony losses are of significant international concern because of the essential role these insects play in pollinating many high nutrient crops, such as fruits, vegetables, and nuts. Both chemical and non-chemical stressors have been implicated as possible contributors to colony failure, however, the potential role(s) of commonly-used neonicotinoid insecticides has emerged as particularly concerning. Neonicotinoids act on the nicotinic acetylcholine receptors (nAChRs) in the central nervous system to eliminate target pest insects. However, mounting evidence indicates that these neonicotinoids also may adversely affect beneficial pollinators, such as the honey bee, via impairments on learning and memory, and ultimately foraging success. The specific mechanisms linking activation of the nAChR to adverse effects on learning and memory are uncertain. Additionally, clear connections between observed impacts on individual bees and colony level effects are lacking. The objective of this review was to develop adverse outcome pathways (AOPs) as a means to evaluate the biological plausibility and empirical evidence supporting (or refuting) the linkage between activation of the physiological target site, the nAChR, and colony level consequences. Development of AOPs has led to the identification of research gaps which, for example, may be of high priority in understanding how perturbation of pathways involved in neurotransmission can adversely affect norm

Based on Fuzzy Comprehensive Evaluation Method The Investment Risk Assessment of Chinese Enterprises in The Countries Along “The Belt and Road”

NASA Astrophysics Data System (ADS)

Chen, Yanyu; Chai, Huaqi; Huang, Yimiao

2018-01-01

“Belt and Road Forum for International Cooperation” held in Beijing in May this year. once again, “The Belt and Road” strategic initiative to the world, causing the world’s enthusiastic response. The core of the “One Belt, One Road” strategy initiative is to promote infrastructure construction and interconnection, dock national policies and development strategies, deepen pragmatic cooperation, promote coordinated and coordinated development and achieve common prosperity. With the “The Belt and Road” strategy in-depth, Chinese enterprises will go abroad, in the countries along the country to invest in more and more examples, accompanied by the increasing risk. Analysis of the failure of investment cases, we can easily find that this is the majority of enterprises overseas investment in the lack of careful assessment of risk and risk of foreign investment risk management has a great relationship. In this paper, the risk factors are used to identify the risk factors table, and the fuzzy comprehensive evaluation method is used to estimate the comprehensive risk value of many uncertain factors that cannot be determined by the overseas investment. The risk assessment system is constructed to help Chinese enterprises to follow the " Investment to avoid risks, improve the success rate.

Learning accurate very fast decision trees from uncertain data streams

NASA Astrophysics Data System (ADS)

Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

2015-12-01

Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

Time evolving multi-city dependencies and robustness tradeoffs for risk-based portfolios of conservation, transfers, and cooperative water supply infrastructure development pathways

NASA Astrophysics Data System (ADS)

Trindade, B. C.; Reed, P. M.; Zeff, H. B.; Characklis, G. W.

2016-12-01

Water scarcity in historically water-rich regions such as the southeastern United States is becoming a more prevalent concern. It has been shown that cooperative short-term planning that relies on conservation and transfers of existing supplies amongst communities can be used by water utilities to mitigate the effects of water scarcity in the near future. However, in the longer term, infrastructure expansion is likely to be necessary to address imbalances between growing water demands and the available supply capacity. This study seeks to better diagnose and avoid candidate modes for system failure. Although it is becoming more common for water utilities to evaluate the robustness of their water supply, defined as the insensitivity of their systems to errors in deeply uncertain projections or assumptions, defining robustness is particularly challenging in multi-stakeholder regional contexts for decisions that encompass short management actions and long-term infrastructure planning. Planning and management decisions are highly interdependent and strongly shape how a region's infrastructure itself evolves. This research advances the concept of system robustness by making it evolve over time rather than static, so that it is applicable to an adaptive system and therefore more suited for use for combined short and long-term planning efforts. The test case for this research is the Research Triangle area of North Carolina, where the cities of Raleigh, Durham, Cary and Chapel Hill are experiencing rapid population growth and increasing concerns over drought. This study is facilitating their engagement in cooperative and robust regional water portfolio planning. The insights from this work have general merit for regions where adjacent municipalities can benefit from improving cooperative infrastructure investments and more efficient resource management strategies.

Robust stochastic fuzzy possibilistic programming for environmental decision making under uncertainty.

PubMed

Zhang, Xiaodong; Huang, Guo H; Nie, Xianghui

2009-12-20

Nonpoint source (NPS) water pollution is one of serious environmental issues, especially within an agricultural system. This study aims to propose a robust chance-constrained fuzzy possibilistic programming (RCFPP) model for water quality management within an agricultural system, where solutions for farming area, manure/fertilizer application amount, and livestock husbandry size under different scenarios are obtained and interpreted. Through improving upon the existing fuzzy possibilistic programming, fuzzy robust programming and chance-constrained programming approaches, the RCFPP can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original fuzzy constraints, the RCFPP enhances the robustness of the optimization processes and resulting solutions. The results of the case study indicate that useful information can be obtained through the proposed RCFPP model for providing feasible decision schemes for different agricultural activities under different scenarios (combinations of different p-necessity and p(i) levels). A p-necessity level represents the certainty or necessity degree of the imprecise objective function, while a p(i) level means the probabilities at which the constraints will be violated. A desire to acquire high agricultural income would decrease the certainty degree of the event that maximization of the objective be satisfied, and potentially violate water management standards; willingness to accept low agricultural income will run into the risk of potential system failure. The decision variables under combined p-necessity and p(i) levels were useful for the decision makers to justify and/or adjust the decision schemes for the agricultural activities through incorporation of their implicit knowledge. The results also suggest that this developed approach is applicable to many practical problems where fuzzy and probabilistic distribution information simultaneously exist.

After Decentralization: Delimitations and Possibilities within New Fields

ERIC Educational Resources Information Center

Wahlstrom, Ninni

2008-01-01

The shift from a centralized to a decentralized school system can be seen as a solution to an uncertain problem. Through analysing the displacements in the concept of equivalence within Sweden's decentralized school system, this study illustrates how the meaning of the concept of equivalence shifts over time, from a more collective target…

Aircraft Alerting Systems Criteria Study. Volume II. Human Factors Guidelines for Aircraft Alerting Systems

DTIC Science & Technology

1977-05-01

Effect of Mixing Flashing and Steady Irrelevant Lights, Ergonomics, Vol. 6 (3), 1963, pp. 27-294. Creelman , C. D., Detection of Signals of Uncertain...Frequency, Acoustical Sok. America-J, Vol. 32 (7), July 1960, pp. 805-10. Creelman , C. D., Detection, Discrimination, and Loudness of Short Tones

A Framework For Analyzing And Mitigating The Vulnerabilities Of Complex Systems Via Attack And Protection Trees

DTIC Science & Technology

2007-07-01

Systems, Ciudad Real, Spain, 2002. [Ame00] "Metamorphosis," in American Heritage Dictionary of the English Language Fourth ed: Houghton Mifflin Company...Beyond Fear: Thinking Sensibly About Security in an Uncertain World. New York: Copernicus Books, 2003. [Sch99] Schneier, B. "Modeling Security

An optimization approach for observation association with systemic uncertainty applied to electro-optical systems

NASA Astrophysics Data System (ADS)

Worthy, Johnny L.; Holzinger, Marcus J.; Scheeres, Daniel J.

2018-06-01

The observation to observation measurement association problem for dynamical systems can be addressed by determining if the uncertain admissible regions produced from each observation have one or more points of intersection in state space. An observation association method is developed which uses an optimization based approach to identify local Mahalanobis distance minima in state space between two uncertain admissible regions. A binary hypothesis test with a selected false alarm rate is used to assess the probability that an intersection exists at the point(s) of minimum distance. The systemic uncertainties, such as measurement uncertainties, timing errors, and other parameter errors, define a distribution about a state estimate located at the local Mahalanobis distance minima. If local minima do not exist, then the observations are not associated. The proposed method utilizes an optimization approach defined on a reduced dimension state space to reduce the computational load of the algorithm. The efficacy and efficiency of the proposed method is demonstrated on observation data collected from the Georgia Tech Space Object Research Telescope.

Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

Stability and Performance Metrics for Adaptive Flight Control

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

2009-01-01

This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

A Novel Finite-Sum Inequality-Based Method for Robust H∞ Control of Uncertain Discrete-Time Takagi-Sugeno Fuzzy Systems With Interval-Like Time-Varying Delays.

PubMed

Zhang, Xian-Ming; Han, Qing-Long; Ge, Xiaohua

2017-09-22

This paper is concerned with the problem of robust H∞ control of an uncertain discrete-time Takagi-Sugeno fuzzy system with an interval-like time-varying delay. A novel finite-sum inequality-based method is proposed to provide a tighter estimation on the forward difference of certain Lyapunov functional, leading to a less conservative result. First, an auxiliary vector function is used to establish two finite-sum inequalities, which can produce tighter bounds for the finite-sum terms appearing in the forward difference of the Lyapunov functional. Second, a matrix-based quadratic convex approach is employed to equivalently convert the original matrix inequality including a quadratic polynomial on the time-varying delay into two boundary matrix inequalities, which delivers a less conservative bounded real lemma (BRL) for the resultant closed-loop system. Third, based on the BRL, a novel sufficient condition on the existence of suitable robust H∞ fuzzy controllers is derived. Finally, two numerical examples and a computer-simulated truck-trailer system are provided to show the effectiveness of the obtained results.

A Design Heritage-Based Forecasting Methodology for Risk Informed Management of Advanced Systems

NASA Technical Reports Server (NTRS)

Maggio, Gaspare; Fragola, Joseph R.

1999-01-01

The development of next generation systems often carries with it the promise of improved performance, greater reliability, and reduced operational costs. These expectations arise from the use of novel designs, new materials, advanced integration and production technologies intended for functionality replacing the previous generation. However, the novelty of these nascent technologies is accompanied by lack of operational experience and, in many cases, no actual testing as well. Therefore some of the enthusiasm surrounding most new technologies may be due to inflated aspirations from lack of knowledge rather than actual future expectations. This paper proposes a design heritage approach for improved reliability forecasting of advanced system components. The basis of the design heritage approach is to relate advanced system components to similar designs currently in operation. The demonstrated performance of these components could then be used to forecast the expected performance and reliability of comparable advanced technology components. In this approach the greater the divergence of the advanced component designs from the current systems the higher the uncertainty that accompanies the associated failure estimates. Designers of advanced systems are faced with many difficult decisions. One of the most common and more difficult types of these decisions are those related to the choice between design alternatives. In the past decision-makers have found these decisions to be extremely difficult to make because they often involve the trade-off between a known performing fielded design and a promising paper design. When it comes to expected reliability performance the paper design always looks better because it is on paper and it addresses all the know failure modes of the fielded design. On the other hand there is a long, and sometimes very difficult road, between the promise of a paper design and its fulfillment; with the possibility that sometimes the reliability promise is not fulfilled at all. Decision makers in advanced technology areas have always known to discount the performance claims of a design to a degree in proportion to its stage of development, and at times have preferred the more mature design over the one of lesser maturity even with the latter promising substantially better performance once fielded. As with the broader measures of performance this has also been true for projected reliability performance. Paper estimates of potential advances in design reliability are to a degree uncertain in proportion to the maturity of the features being proposed to secure those advances. This is especially true when performance-enhancing features in other areas are also planned to be part of the development program.

Cause-specific risk of hospital admission related to extreme heat in older adults.

PubMed

Bobb, Jennifer F; Obermeyer, Ziad; Wang, Yun; Dominici, Francesca

Heat exposure is known to have a complex set of physiological effects on multiple organ systems, but current understanding of the health effects is mostly based on studies investigating a small number of prespecified health outcomes such as cardiovascular and respiratory diseases. To identify possible causes of hospital admissions during extreme heat events and to estimate their risks using historical data. Matched analysis of time series data describing daily hospital admissions of Medicare enrollees (23.7 million fee-for-service beneficiaries [aged ≥65 years] per year; 85% of all Medicare enrollees) for the period 1999 to 2010 in 1943 counties in the United States with at least 5 summers of near-complete (>95%) daily temperature data. Heat wave periods, defined as 2 or more consecutive days with temperatures exceeding the 99th percentile of county-specific daily temperatures, matched to non-heat wave periods by county and week. Daily cause-specific hospitalization rates by principal discharge diagnosis codes, grouped into 283 disease categories using a validated approach. Risks of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke were statistically significantly higher on heat wave days relative to matched non-heat wave days, but risk of hospitalization for congestive heart failure was lower (P < .05). Relative risks for these disease groups were 1.18 (95% CI, 1.12-1.25) for fluid and electrolyte disorders, 1.14 (95% CI, 1.06-1.23) for renal failure, 1.10 (95% CI, 1.04-1.16) for urinary tract infections, 1.06 (95% CI, 1.00-1.11) for septicemia, and 2.54 (95% CI, 2.14-3.01) for heat stroke. Absolute risk differences were 0.34 (95% CI, 0.22-0.46) excess admissions per 100,000 individuals at risk for fluid and electrolyte disorders, 0.25 (95% CI, 0.12-0.39) for renal failure, 0.24 (95% CI, 0.09-0.39) for urinary tract infections, 0.21 (95% CI, 0.01-0.41) for septicemia, and 0.16 (95% CI, 0.10-0.22) for heat stroke. For fluid and electrolyte disorders and heat stroke, the risk of hospitalization increased during more intense and longer-lasting heat wave periods (P < .05). Risks were generally highest on the heat wave day but remained elevated for up to 5 subsequent days. Among older adults, periods of extreme heat were associated with increased risk of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke. However, the absolute risk increase was small and of uncertain clinical importance.

Cause-Specific Risk of Hospital Admission Related to Extreme Heat in Older Adults

PubMed Central

Bobb, Jennifer F.; Obermeyer, Ziad; Wang, Yun; Dominici, Francesca

2015-01-01

IMPORTANCE Heat exposure is known to have a complex set of physiological effects on multiple organ systems, but current understanding of the health effects is mostly based on studies investigating a small number of prespecified health outcomes such as cardiovascular and respiratory diseases. OBJECTIVES To identify possible causes of hospital admissions during extreme heat events and to estimate their risks using historical data. DESIGN, SETTING, AND POPULATION Matched analysis of time series data describing daily hospital admissions of Medicare enrollees (23.7 million fee-for-service beneficiaries [aged ≥65 years] per year; 85% of all Medicare enrollees) for the period 1999 to 2010 in 1943 counties in the United States with at least 5 summers of near-complete (>95%) daily temperature data. EXPOSURES Heat wave periods, defined as 2 or more consecutive days with temperatures exceeding the 99th percentile of county-specific daily temperatures, matched to non–heat wave periods by county and week. MAIN OUTCOMES AND MEASURES Daily cause-specific hospitalization rates by principal discharge diagnosis codes, grouped into 283 disease categories using a validated approach. RESULTS Risks of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke were statistically significantly higher on heat wave days relative to matched non–heat wave days, but risk of hospitalization for congestive heart failure was lower (P < .05). Relative risks for these disease groups were 1.18 (95% CI, 1.12–1.25) for fluid and electrolyte disorders, 1.14 (95% CI, 1.06–1.23) for renal failure, 1.10 (95% CI, 1.04–1.16) for urinary tract infections, 1.06 (95% CI, 1.00–1.11) for septicemia, and 2.54 (95% CI, 2.14–3.01) for heat stroke. Absolute risk differences were 0.34 (95% CI, 0.22–0.46) excess admissions per 100 000 individuals at risk for fluid and electrolyte disorders, 0.25 (95% CI, 0.12–0.39) for renal failure, 0.24 (95% CI, 0.09–0.39) for urinary tract infections, 0.21 (95% CI, 0.01–0.41) for septicemia, and 0.16 (95% CI, 0.10–0.22) for heat stroke. For fluid and electrolyte disorders and heat stroke, the risk of hospitalization increased during more intense and longer-lasting heat wave periods (P < .05). Risks were generally highest on the heat wave day but remained elevated for up to 5 subsequent days. CONCLUSIONS AND RELEVANCE Among older adults, periods of extreme heat were associated with increased risk of hospitalization for fluid and electrolyte disorders, renal failure, urinary tract infection, septicemia, and heat stroke. However, the absolute risk increase was small and of uncertain clinical importance. PMID:25536257

Graphical Displays Assist In Analysis Of Failures

NASA Technical Reports Server (NTRS)

Pack, Ginger; Wadsworth, David; Razavipour, Reza

1995-01-01

Failure Environment Analysis Tool (FEAT) computer program enables people to see and better understand effects of failures in system. Uses digraph models to determine what will happen to system if set of failure events occurs and to identify possible causes of selected set of failures. Digraphs or engineering schematics used. Also used in operations to help identify causes of failures after they occur. Written in C language.

A global parallel model based design of experiments method to minimize model output uncertainty.

PubMed

Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E

2012-03-01

Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.

Sensor Failure Detection of FASSIP System using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Sudarno; Juarsa, Mulya; Santosa, Kussigit; Deswandri; Sunaryo, Geni Rina

2018-02-01

In the nuclear reactor accident of Fukushima Daiichi in Japan, the damages of core and pressure vessel were caused by the failure of its active cooling system (diesel generator was inundated by tsunami). Thus researches on passive cooling system for Nuclear Power Plant are performed to improve the safety aspects of nuclear reactors. The FASSIP system (Passive System Simulation Facility) is an installation used to study the characteristics of passive cooling systems at nuclear power plants. The accuracy of sensor measurement of FASSIP system is essential, because as the basis for determining the characteristics of a passive cooling system. In this research, a sensor failure detection method for FASSIP system is developed, so the indication of sensor failures can be detected early. The method used is Principal Component Analysis (PCA) to reduce the dimension of the sensor, with the Squarred Prediction Error (SPE) and statistic Hotteling criteria for detecting sensor failure indication. The results shows that PCA method is capable to detect the occurrence of a failure at any sensor.

Resilience Engineering in Critical Long Term Aerospace Software Systems: A New Approach to Spacecraft Software Safety

NASA Astrophysics Data System (ADS)

Dulo, D. A.

Safety critical software systems permeate spacecraft, and in a long term venture like a starship would be pervasive in every system of the spacecraft. Yet software failure today continues to plague both the systems and the organizations that develop them resulting in the loss of life, time, money, and valuable system platforms. A starship cannot afford this type of software failure in long journeys away from home. A single software failure could have catastrophic results for the spaceship and the crew onboard. This paper will offer a new approach to developing safe reliable software systems through focusing not on the traditional safety/reliability engineering paradigms but rather by focusing on a new paradigm: Resilience and Failure Obviation Engineering. The foremost objective of this approach is the obviation of failure, coupled with the ability of a software system to prevent or adapt to complex changing conditions in real time as a safety valve should failure occur to ensure safe system continuity. Through this approach, safety is ensured through foresight to anticipate failure and to adapt to risk in real time before failure occurs. In a starship, this type of software engineering is vital. Through software developed in a resilient manner, a starship would have reduced or eliminated software failure, and would have the ability to rapidly adapt should a software system become unstable or unsafe. As a result, long term software safety, reliability, and resilience would be present for a successful long term starship mission.

Cluster synchronization transmission of different external signals in discrete uncertain network

NASA Astrophysics Data System (ADS)

Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

2018-07-01

We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

Adaptive optimization as a design and management methodology for coal-mining enterprise in uncertain and volatile market environment - the conceptual framework

NASA Astrophysics Data System (ADS)

Mikhalchenko, V. V.; Rubanik, Yu T.

2016-10-01

The work is devoted to the problem of cost-effective adaptation of coal mines to the volatile and uncertain market conditions. Conceptually it can be achieved through alignment of the dynamic characteristics of the coal mining system and power spectrum of market demand for coal product. In practical terms, this ensures the viability and competitiveness of coal mines. Transformation of dynamic characteristics is to be done by changing the structure of production system as well as corporate, logistics and management processes. The proposed methods and algorithms of control are aimed at the development of the theoretical foundations of adaptive optimization as basic methodology for coal mine enterprise management in conditions of high variability and uncertainty of economic and natural environment. Implementation of the proposed methodology requires a revision of the basic principles of open coal mining enterprises design.

H∞ control for uncertain linear system over networks with Bernoulli data dropout and actuator saturation.

PubMed

Yu, Jimin; Yang, Chenchen; Tang, Xiaoming; Wang, Ping

2018-03-01

This paper investigates the H ∞ control problems for uncertain linear system over networks with random communication data dropout and actuator saturation. The random data dropout process is modeled by a Bernoulli distributed white sequence with a known conditional probability distribution and the actuator saturation is confined in a convex hull by introducing a group of auxiliary matrices. By constructing a quadratic Lyapunov function, effective conditions for the state feedback-based H ∞ controller and the observer-based H ∞ controller are proposed in the form of non-convex matrix inequalities to take the random data dropout and actuator saturation into consideration simultaneously, and the problem of non-convex feasibility is solved by applying cone complementarity linearization (CCL) procedure. Finally, two simulation examples are given to demonstrate the effectiveness of the proposed new design techniques. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Uncertainty Quantification in Aeroelasticity

NASA Astrophysics Data System (ADS)

Beran, Philip; Stanford, Bret; Schrock, Christopher

2017-01-01

Physical interactions between a fluid and structure, potentially manifested as self-sustained or divergent oscillations, can be sensitive to many parameters whose values are uncertain. Of interest here are aircraft aeroelastic interactions, which must be accounted for in aircraft certification and design. Deterministic prediction of these aeroelastic behaviors can be difficult owing to physical and computational complexity. New challenges are introduced when physical parameters and elements of the modeling process are uncertain. By viewing aeroelasticity through a nondeterministic prism, where key quantities are assumed stochastic, one may gain insights into how to reduce system uncertainty, increase system robustness, and maintain aeroelastic safety. This article reviews uncertainty quantification in aeroelasticity using traditional analytical techniques not reliant on computational fluid dynamics; compares and contrasts this work with emerging methods based on computational fluid dynamics, which target richer physics; and reviews the state of the art in aeroelastic optimization under uncertainty. Barriers to continued progress, for example, the so-called curse of dimensionality, are discussed.

Robust optimization based energy dispatch in smart grids considering demand uncertainty

NASA Astrophysics Data System (ADS)

Nassourou, M.; Puig, V.; Blesa, J.

2017-01-01

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Life Prediction of Spent Fuel Storage Canister Material

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

Ballinger, Ronald

The original purpose of this project was to develop a probabilistic model for SCC-induced failure of spent fuel storage canisters, exposed to a salt-air environment in the temperature range 30-70°C for periods up to and exceeding 100 years. The nature of this degradation process, which involves multiple degradation mechanisms, combined with variable and uncertain environmental conditions dictates a probabilistic approach to life prediction. A final report for the original portion of the project was submitted earlier. However, residual stress measurements for as-welded and repair welds could not be performed within the original time of the project. As a result ofmore » this, a no-cost extension was granted in order to complete these tests. In this report, we report on the results of residual stress measurements.« less

Tractable Experiment Design via Mathematical Surrogates

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

Williams, Brian J.

This presentation summarizes the development and implementation of quantitative design criteria motivated by targeted inference objectives for identifying new, potentially expensive computational or physical experiments. The first application is concerned with estimating features of quantities of interest arising from complex computational models, such as quantiles or failure probabilities. A sequential strategy is proposed for iterative refinement of the importance distributions used to efficiently sample the uncertain inputs to the computational model. In the second application, effective use of mathematical surrogates is investigated to help alleviate the analytical and numerical intractability often associated with Bayesian experiment design. This approach allows formore » the incorporation of prior information into the design process without the need for gross simplification of the design criterion. Illustrative examples of both design problems will be presented as an argument for the relevance of these research problems.« less

Butyrfentanyl overdose resulting in diffuse alveolar hemorrhage.

PubMed

Cole, Jon B; Dunbar, John F; McIntire, Sarah A; Regelmann, Warren E; Slusher, Tina M

2015-03-01

Butyrfentanyl is a potent short-acting opioid and a fentanyl analog with uncertain clinical effects. A review of the literature reveals no human case reports of butyrfentanyl overdose. As the use of analog and synthetic drugs continues to increase, clinicians are often faced with tremendous uncertainty when they encounter patients exposed to these synthetic drugs. We describe, to our knowledge, the first case of a butyrfentanyl overdose that resulted in clinically significant hemoptysis, acute lung injury, hypoxic respiratory failure, and diffuse alveolar hemorrhage. Complicating this case was a false-positive urine drug screen for fentanyl. Clinicians who encounter fentanyl exposures should be aware they may in fact be dealing with butyrfentanyl. As little is known of butyrfentanyl and our patient suffered a significant pulmonary hemorrhage, those who encounter butyrfentanyl exposures should monitor for hemorrhagic complications. Copyright © 2015 by the American Academy of Pediatrics.

Margins Associated with Loss of Assured Safety for Systems with Multiple Time-Dependent Failure Modes.

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

Helton, Jon C.; Brooks, Dusty Marie; Sallaberry, Cedric Jean-Marie.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) – (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property valuemore » at which SL system fails) – (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) – (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.« less

Load fatigue performance of four implant-abutment interface designs: effect of torque level and implant system.

PubMed

Quek, H C; Tan, Keson B; Nicholls, Jack I

2008-01-01

Biomechanical load-fatigue performance data on single-tooth implant systems with different implant-abutment interface designs is lacking in the literature. This study evaluated the load fatigue performance of 4 implant-abutment interface designs (Brånemark-CeraOne; 3i Osseotite-STA abutment; Replace Select-Easy abutment; and Lifecore Stage-1-COC abutment system). The number of load cycles to fatigue failure of 4 implant-abutment designs was tested with a custom rotational load fatigue machine. The effect of increasing and decreasing the tightening torque by 20% respectively on the load fatigue performance was also investigated. Three different tightening torque levels (recommended torque, -20% recommended torque, +20% recommended torque) were applied to the 4 implant systems. There were 12 test groups with 5 samples in each group. The rotational load fatigue machine subjected specimens to a sinusoidally applied 35 Ncm bending moment at a test frequency of 14 Hz. The number of cycles to failure was recorded. A cutoff of 5 x 10(6) cycles was applied as an upper limit. There were 2 implant failures and 1 abutment screw failure in the Brånemark group. Five abutment screw failures and 4 implant failures was recorded for the 3i system. The Replace Select system had 1 implant failure. Five cone screw failures were noted for the Lifecore system. Analysis of variance revealed no statistically significant difference in load cycles to failure for the 4 different implant-abutment systems torqued at recommended torque level. A statistically significant difference was found between the -20% torque group and the +20% torque group (P < .05) for the 3i system. Load fatigue performance and failure location is system specific and related to the design characteristics of the implant-abutment combination. It appeared that if the implant-abutment interface was maintained, load fatigue failure would occur at the weakest point of the implant. It is important to use the torque level recommended by the manufacturer.

Impossible Certainty: Cost Risk Analysis for Air Force Systems

DTIC Science & Technology

2006-01-01

the estimated cost of weapon systems , which typically take many years to acquire and remain in operation for a long time . To make those esti- mates... times , uncertain, undefined, or unknown when estimates are prepared. New system development may involve further uncer- tainty due to unproven or...risk (a system requiring more money to complete than was forecasted ) and opera- tional risk (a vital capability becoming unaffordable as the program

Generalized Distributed Consensus-based Algorithms for Uncertain Systems and Networks

DTIC Science & Technology

2010-01-01

time linear systems with markovian jumping parameters and additive disturbances. SIAM Journal on Control and Optimization, 44(4):1165– 1191, 2005... time marko- vian jump linear systems , in the presence of delayed mode observations. Proceed- ings of the 2008 IEEE American Control Conference, pages...Markovian Jump Linear System state estimation . . . . 147 6 Conclusions 152 A Discrete- Time Coupled Matrix Equations 156 A.1 Properties of a special

Optimal Regulation of Structural Systems with Uncertain Parameters.

DTIC Science & Technology

1981-02-02

been addressed, in part, by Statistical Energy Analysis . Moti- vated by a concern with high frequency vibration and acoustical- structural...Parameter Systems," AFOSR-TR-79-0753 (May, 1979). 25. R. H. Lyon, Statistical Energy Analysis of Dynamical Systems: Theory and Applications, (M.I.T...Press, Cambridge, Mass., 1975). 26. E. E. Ungar, " Statistical Energy Analysis of Vibrating Systems," Trans. ASME, J. Eng. Ind. 89, 626 (1967). 139 27

State-dependent resource harvesting with lagged information about system states

USGS Publications Warehouse

Johnson, Fred A.; Fackler, Paul L.; Boomer, G Scott; Zimmerman, Guthrie S.; Williams, Byron K.; Nichols, James D.; Dorazio, Robert

2016-01-01

Markov decision processes (MDPs), which involve a temporal sequence of actions conditioned on the state of the managed system, are increasingly being applied in natural resource management. This study focuses on the modification of a traditional MDP to account for those cases in which an action must be chosen after a significant time lag in observing system state, but just prior to a new observation. In order to calculate an optimal decision policy under these conditions, possible actions must be conditioned on the previous observed system state and action taken. We show how to solve these problems when the state transition structure is known and when it is uncertain. Our focus is on the latter case, and we show how actions must be conditioned not only on the previous system state and action, but on the probabilities associated with alternative models of system dynamics. To demonstrate this framework, we calculated and simulated optimal, adaptive policies for MDPs with lagged states for the problem of deciding annual harvest regulations for mallards (Anas platyrhynchos) in the United States. In this particular example, changes in harvest policy induced by the use of lagged information about system state were sufficient to maintain expected management performance (e.g. population size, harvest) even in the face of an uncertain system state at the time of a decision.

Extended Testability Analysis Tool

NASA Technical Reports Server (NTRS)

Melcher, Kevin; Maul, William A.; Fulton, Christopher

2012-01-01

The Extended Testability Analysis (ETA) Tool is a software application that supports fault management (FM) by performing testability analyses on the fault propagation model of a given system. Fault management includes the prevention of faults through robust design margins and quality assurance methods, or the mitigation of system failures. Fault management requires an understanding of the system design and operation, potential failure mechanisms within the system, and the propagation of those potential failures through the system. The purpose of the ETA Tool software is to process the testability analysis results from a commercial software program called TEAMS Designer in order to provide a detailed set of diagnostic assessment reports. The ETA Tool is a command-line process with several user-selectable report output options. The ETA Tool also extends the COTS testability analysis and enables variation studies with sensor sensitivity impacts on system diagnostics and component isolation using a single testability output. The ETA Tool can also provide extended analyses from a single set of testability output files. The following analysis reports are available to the user: (1) the Detectability Report provides a breakdown of how each tested failure mode was detected, (2) the Test Utilization Report identifies all the failure modes that each test detects, (3) the Failure Mode Isolation Report demonstrates the system s ability to discriminate between failure modes, (4) the Component Isolation Report demonstrates the system s ability to discriminate between failure modes relative to the components containing the failure modes, (5) the Sensor Sensor Sensitivity Analysis Report shows the diagnostic impact due to loss of sensor information, and (6) the Effect Mapping Report identifies failure modes that result in specified system-level effects.

CPLOAS_2 User Manual.

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

Sallaberry, Cedric Jean-Marie; Helton, Jon C.

2015-05-01

Weak link (WL)/strong link (SL) systems are important parts of the overall operational design of high - consequence systems. In such designs, the SL system is very robust and is intended to permit operation of the entire system under, and only under, intended conditions. In contrast, the WL system is intended to fail in a predictable and irreversible manner under accident conditions and render the entire system inoperable before an accidental operation of the SL system. The likelihood that the WL system will fail to d eactivate the entire system before the SL system fails (i.e., degrades into a configurationmore » that could allow an accidental operation of the entire system) is referred to as probability of loss of assured safety (PLOAS). This report describes the Fortran 90 program CPLOAS_2 that implements the following representations for PLOAS for situations in which both link physical properties and link failure properties are time - dependent: (i) failure of all SLs before failure of any WL, (ii) failure of any SL before f ailure of any WL, (iii) failure of all SLs before failure of all WLs, and (iv) failure of any SL before failure of all WLs. The effects of aleatory uncertainty and epistemic uncertainty in the definition and numerical evaluation of PLOAS can be included in the calculations performed by CPLOAS_2. Keywords: Aleatory uncertainty, CPLOAS_2, Epistemic uncertainty, Probability of loss of assured safety, Strong link, Uncertainty analysis, Weak link« less

Independent Orbiter Assessment (IOA): Analysis of the purge, vent and drain subsystem

NASA Technical Reports Server (NTRS)

Bynum, M. C., III

1987-01-01

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter PV and D (Purge, Vent and Drain) Subsystem hardware. The PV and D Subsystem controls the environment of unpressurized compartments and window cavities, senses hazardous gases, and purges Orbiter/ET Disconnect. The subsystem is divided into six systems: Purge System (controls the environment of unpressurized structural compartments); Vent System (controls the pressure of unpressurized compartments); Drain System (removes water from unpressurized compartments); Hazardous Gas Detection System (HGDS) (monitors hazardous gas concentrations); Window Cavity Conditioning System (WCCS) (maintains clear windows and provides pressure control of the window cavities); and External Tank/Orbiter Disconnect Purge System (prevents cryo-pumping/icing of disconnect hardware). Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. Four of the sixty-two failure modes analyzed were determined as single failures which could result in the loss of crew or vehicle. A possible loss of mission could result if any of twelve single failures occurred. Two of the criticality 1/1 failures are in the Window Cavity Conditioning System (WCCS) outer window cavity, where leakage and/or restricted flow will cause failure to depressurize/repressurize the window cavity. Two criticality 1/1 failures represent leakage and/or restricted flow in the Orbiter/ET disconnect purge network which prevent cryopumping/icing of disconnect hardware. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Robust H ∞ Control for Spacecraft Rendezvous with a Noncooperative Target

PubMed Central

Wu, Shu-Nan; Zhou, Wen-Ya; Tan, Shu-Jun; Wu, Guo-Qiang

2013-01-01

The robust H ∞ control for spacecraft rendezvous with a noncooperative target is addressed in this paper. The relative motion of chaser and noncooperative target is firstly modeled as the uncertain system, which contains uncertain orbit parameter and mass. Then the H ∞ performance and finite time performance are proposed, and a robust H ∞ controller is developed to drive the chaser to rendezvous with the non-cooperative target in the presence of control input saturation, measurement error, and thrust error. The linear matrix inequality technology is used to derive the sufficient condition of the proposed controller. An illustrative example is finally provided to demonstrate the effectiveness of the controller. PMID:24027446

Generic Sensor Failure Modeling for Cooperative Systems.

PubMed

Jäger, Georg; Zug, Sebastian; Casimiro, António

2018-03-20

The advent of cooperative systems entails a dynamic composition of their components. As this contrasts current, statically composed systems, new approaches for maintaining their safety are required. In that endeavor, we propose an integration step that evaluates the failure model of shared information in relation to an application's fault tolerance and thereby promises maintainability of such system's safety. However, it also poses new requirements on failure models, which are not fulfilled by state-of-the-art approaches. Consequently, this work presents a mathematically defined generic failure model as well as a processing chain for automatically extracting such failure models from empirical data. By examining data of an Sharp GP2D12 distance sensor, we show that the generic failure model not only fulfills the predefined requirements, but also models failure characteristics appropriately when compared to traditional techniques.

Quantitative method of medication system interface evaluation.

PubMed

Pingenot, Alleene Anne; Shanteau, James; Pingenot, James D F

2007-01-01

The objective of this study was to develop a quantitative method of evaluating the user interface for medication system software. A detailed task analysis provided a description of user goals and essential activity. A structural fault analysis was used to develop a detailed description of the system interface. Nurses experienced with use of the system under evaluation provided estimates of failure rates for each point in this simplified fault tree. Means of estimated failure rates provided quantitative data for fault analysis. Authors note that, although failures of steps in the program were frequent, participants reported numerous methods of working around these failures so that overall system failure was rare. However, frequent process failure can affect the time required for processing medications, making a system inefficient. This method of interface analysis, called Software Efficiency Evaluation and Fault Identification Method, provides quantitative information with which prototypes can be compared and problems within an interface identified.

Models and mechanisms of anxiety: evidence from startle studies

PubMed Central

Grillon, Christian

2009-01-01

Rationale Preclinical data indicates that threat stimuli elicit two classes of defensive behaviors, those that are associated with imminent danger and are characterized by avoidance or fight (fear), and those that are associated with temporally uncertain danger and are characterized by sustained apprehension and hypervigilance (anxiety). Objective To 1) review evidence for a distinction between fear and anxiety in animal and human experimental models using the startle reflex as an operational measure of aversive states, 2) describe experimental models of anxiety, as opposed to fear, in humans, 3) examine the relevance of these models to clinical anxiety. Results The distinction between phasic fear to imminent threat and sustained anxiety to temporally uncertain danger is suggested by psychopharmacological and behavioral evidence from ethological studies and can be traced back to distinct neuroanatomical systems, the amygdala and the bed nucleus of the stria terminalis. Experimental models of anxiety, not fear, are relevant to non-phobic anxiety disorders. Conclusions Progress in our understanding of normal and abnormal anxiety is critically dependent on our ability to model sustained aversive states to temporally uncertain threat. PMID:18058089

Pre-cue Fronto-Occipital Alpha Phase and Distributed Cortical Oscillations Predict Failures of Cognitive Control

PubMed Central

Hamm, Jordan P.; Dyckman, Kara A.; McDowell, Jennifer E.; Clementz, Brett A.

2012-01-01

Cognitive control is required for correct performance on antisaccade tasks, including the ability to inhibit an externally driven ocular motor repsonse (a saccade to a peripheral stimulus) in favor of an internally driven ocular motor goal (a saccade directed away from a peripheral stimulus). Healthy humans occasionally produce errors during antisaccade tasks, but the mechanisms associated with such failures of cognitive control are uncertain. Most research on cognitive control failures focuses on post-stimulus processing, although a growing body of literature highlights a role of intrinsic brain activity in perceptual and cognitive performance. The current investigation used dense array electroencephalography and distributed source analyses to examine brain oscillations across a wide frequency bandwidth in the period prior to antisaccade cue onset. Results highlight four important aspects of ongoing and preparatory brain activations that differentiate error from correct antisaccade trials: (i) ongoing oscillatory beta (20–30Hz) power in anterior cingulate prior to trial initiation (lower for error trials), (ii) instantaneous phase of ongoing alpha-theta (7Hz) in frontal and occipital cortices immediately before trial initiation (opposite between trial types), (iii) gamma power (35–60Hz) in posterior parietal cortex 100 ms prior to cue onset (greater for error trials), and (iv) phase locking of alpha (5–12Hz) in parietal and occipital cortices immediately prior to cue onset (lower for error trials). These findings extend recently reported effects of pre-trial alpha phase on perception to cognitive control processes, and help identify the cortical generators of such phase effects. PMID:22593071

Biomechanical Comparison of Single- Versus Double-Row Capsulolabral Repair for Shoulder Instability: A Review

PubMed Central

Yousif, Matthew John; Bicos, James

2017-01-01

Background: The glenohumeral joint is the most commonly dislocated joint in the body. Failure rates of capsulolabral repair have been reported to be approximately 8%. Recent focus has been on restoration of the capsulolabral complex by a double-row capsulolabral repair technique in an effort to decrease redislocation rates after arthroscopic capsulolabral repair. Purpose: To present a review of the biomechanical literature comparing single- versus double-row capsulolabral repairs and discuss the previous case series of double-row fixation. Study Design: Narrative review. Methods: A simple review of the literature was performed by PubMed search. Only biomechanical studies comparing single- versus double-row capsulolabral repair were included for review. Only those case series and descriptive techniques with clinical results for double-row repair were included in the discussion. Results: Biomechanical comparisons evaluating the native footprint of the labrum demonstrated significantly superior restoration of the footprint through double-row capsulolabral repair compared with single-row repair. Biomechanical comparisons of contact pressure at the repair interface, fracture displacement in bony Bankart lesion, load to failure, and decreased external rotation (suggestive of increased load to failure) were also significantly in favor of double- versus single-row repair. Recent descriptive techniques and case series of double-row fixation have demonstrated good clinical outcomes; however, no comparative clinical studies between single- and double-row repair have assessed functional outcomes. Conclusion: The superiority of double-row capsulolabral repair versus single-row repair remains uncertain because comparative studies assessing clinical outcomes have yet to be performed. PMID:29230427

Why miltefosine-a life-saving drug for leishmaniasis-is unavailable to people who need it the most.

PubMed

Sunyoto, Temmy; Potet, Julien; Boelaert, Marleen

2018-01-01

Miltefosine, the only oral drug approved for the treatment of leishmaniasis-a parasitic disease transmitted by sandflies-is considered as a success story of research and development (R&D) by a public-private partnership (PPP). It epitomises the multiple market failures faced by a neglected disease drug: patients with low ability to pay, neglect by authorities and uncertain market size. Originally developed as an anticancer agent in the 1990s, the drug was registered in India in 2002 to treat the fatal visceral leishmaniasis. At the time, miltefosine was considered a breakthrough in the treatment, making it feasible to eliminate a regional disease. Today, access to miltefosine remains far from secure. The initial PPP agreement which includes access to the public sector is not enforced. The reality on the ground has been challenging: shortages due to inefficient supply chains, and use of a substandard product which led to a high number of treatment failures and deaths. Miltefosine received orphan drug status in the USA; when it was registered there in 2014, a priority review voucher (PRV) was awarded. The PRV, meant to facilitate drug development for neglected disease, was subsequently sold to another company for US$125 million without, to date, any apparent impact on drug access. At the heart of these concerns are questions on how to protect societal benefit of a drug developed with public investment, while clinicians worldwide struggle with its lack of affordability, limited availability and sustainability of access. This article analyses the reasons behind the postregistration access failure of miltefosine and provides the lessons learnt.

Lower Mortality in Magnet Hospitals

PubMed Central

McHugh, Matthew D.; Kelly, Lesly A.; Smith, Herbert L.; Wu, Evan S.; Vanak, Jill M.; Aiken, Linda H.

2012-01-01

Background Although there is evidence that hospitals recognized for nursing excellence— Magnet hospitals—are successful in attracting and retaining nurses, it is uncertain whether Magnet recognition is associated with better patient outcomes than non-Magnets, and if so why. Objectives To determine whether Magnet hospitals have lower risk-adjusted mortality and failure-to-rescue compared to non-Magnet hospitals, and to determine the most likely explanations. Method and Study Design Analysis of linked patient, nurse, and hospital data on 56 Magnet and 508 non-Magnet hospitals. Logistic regression models were used to estimate differences in the odds of mortality and failure-to-rescue for surgical patients treated in Magnet vs. non-Magnet hospitals, and to determine the extent to which differences in outcomes can be explained by nursing after accounting for patient and hospital differences. Results Magnet hospitals had significantly better work environments and higher proportions of nurses with bachelor’s degrees and specialty certification. These nursing factors explained much of the Magnet hospital effect on patient outcomes. However, patients treated in Magnet hospitals had 14% lower odds of mortality (OR 0.86, 95% CI 0.76-0.98, p=0.02) and 12% lower odds of failure-to-rescue (OR 0.88, 95% CI 0.77-1.01, p=0.07) while controlling for nursing factors as well as hospital and patient differences. Conclusions Magnet hospitals have lower mortality than is fully accounted for by measured characteristics of nursing. Magnet recognition likely both identifies existing quality and stimulates further positive organizational behavior that improves patient outcomes. PMID:23047129

A diagnosis system using object-oriented fault tree models

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

14 CFR 417.309 - Flight safety system analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... system anomaly occurring and all of its effects as determined by the single failure point analysis and... termination system. (c) Single failure point. A command control system must undergo an analysis that... fault tree analysis or a failure modes effects and criticality analysis; (2) Identify all possible...

Robust Architectures for Complex Multi-Agent Heterogeneous Systems

DTIC Science & Technology

2014-07-23

establish the tradeoff between the control performance and the QoS of the communications network . We also derived the performance bound on the difference...accomplished within this time period leveraged the prior accomplishments in the area of networked multi-agent systems. The past work (prior to 2011...distributed control of uncertain networked systems [3]. Additionally, a preliminary collision avoidance algorithm has been developed for a team of

Deterministic physical systems under uncertain initial conditions: the case of maximum entropy applied to projectile motion

NASA Astrophysics Data System (ADS)

Montecinos, Alejandra; Davis, Sergio; Peralta, Joaquín

2018-07-01

The kinematics and dynamics of deterministic physical systems have been a foundation of our understanding of the world since Galileo and Newton. For real systems, however, uncertainty is largely present via external forces such as friction or lack of precise knowledge about the initial conditions of the system. In this work we focus on the latter case and describe the use of inference methodologies in solving the statistical properties of classical systems subject to uncertain initial conditions. In particular we describe the application of the formalism of maximum entropy (MaxEnt) inference to the problem of projectile motion, given information about the average horizontal range over many realizations. By using MaxEnt we can invert the problem and use the provided information on the average range to reduce the original uncertainty in the initial conditions. Also, additional insight into the initial condition's probabilities, and the projectile path distribution itself, can be achieved based on the value of the average horizontal range. The wide applicability of this procedure, as well as its ease of use, reveals a useful tool with which to revisit a large number of physics problems, from classrooms to frontier research.

Characterizing traffic under uncertain disruptions : an experimental approach.

DOT National Transportation Integrated Search

2013-03-01

The objective of the research is to study long-term traffic patterns under uncertain disruptions using : data collected from human subjects who simultaneously make route choices in controlled PC-based : laboratory experiments. Uncertain disruptions t...

Multimodal network models for robust transportation systems.

DOT National Transportation Integrated Search

2009-10-01

Since transportation infrastructure projects have a lifetime of many decades, project developers must consider : not only the current demand for the project but also the future demand. Future demand is of course uncertain and should : be treated as s...

A Robustly Stabilizing Model Predictive Control Algorithm

NASA Technical Reports Server (NTRS)

Ackmece, A. Behcet; Carson, John M., III

2007-01-01

A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

Approximate Reasoning: Past, Present, Future

DTIC Science & Technology

1990-06-27

This note presents a personal view of the state of the art in the representation and manipulation of imprecise and uncertain information by automated ... processing systems. To contrast their objectives and characteristics with the sound deductive procedures of classical logic, methodologies developed

Vulnerability Management for an Enterprise Resource Planning System

NASA Astrophysics Data System (ADS)

Goel, Shivani; Kiran, Ravi; Garg, Deepak

2012-09-01

Enterprise resource planning (ERP) systems are commonly used in technical educational institutions(TEIs). ERP systems should continue providing services to its users irrespective of the level of failure. There could be many types of failures in the ERP systems. There are different types of measures or characteristics that can be defined for ERP systems to handle the levels of failure. Here in this paper, various types of failure levels are identified along with various characteristics which are concerned with those failures. The relation between all these is summarized. The disruptions causing vulnerabilities in TEIs are identified .A vulnerability management cycle has been suggested along with many commercial and open source vulnerability management tools. The paper also highlights the importance of resiliency in ERP systems in TEIs.

Global resilience analysis of water distribution systems.

PubMed

Diao, Kegong; Sweetapple, Chris; Farmani, Raziyeh; Fu, Guangtao; Ward, Sarah; Butler, David

2016-12-01

Evaluating and enhancing resilience in water infrastructure is a crucial step towards more sustainable urban water management. As a prerequisite to enhancing resilience, a detailed understanding is required of the inherent resilience of the underlying system. Differing from traditional risk analysis, here we propose a global resilience analysis (GRA) approach that shifts the objective from analysing multiple and unknown threats to analysing the more identifiable and measurable system responses to extreme conditions, i.e. potential failure modes. GRA aims to evaluate a system's resilience to a possible failure mode regardless of the causal threat(s) (known or unknown, external or internal). The method is applied to test the resilience of four water distribution systems (WDSs) with various features to three typical failure modes (pipe failure, excess demand, and substance intrusion). The study reveals GRA provides an overview of a water system's resilience to various failure modes. For each failure mode, it identifies the range of corresponding failure impacts and reveals extreme scenarios (e.g. the complete loss of water supply with only 5% pipe failure, or still meeting 80% of demand despite over 70% of pipes failing). GRA also reveals that increased resilience to one failure mode may decrease resilience to another and increasing system capacity may delay the system's recovery in some situations. It is also shown that selecting an appropriate level of detail for hydraulic models is of great importance in resilience analysis. The method can be used as a comprehensive diagnostic framework to evaluate a range of interventions for improving system resilience in future studies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantifying effectiveness of failure prediction and response in HPC systems : methodology and example.

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

Mayo, Jackson R.; Chen, Frank Xiaoxiao; Pebay, Philippe Pierre

2010-06-01

Effective failure prediction and mitigation strategies in high-performance computing systems could provide huge gains in resilience of tightly coupled large-scale scientific codes. These gains would come from prediction-directed process migration and resource servicing, intelligent resource allocation, and checkpointing driven by failure predictors rather than at regular intervals based on nominal mean time to failure. Given probabilistic associations of outlier behavior in hardware-related metrics with eventual failure in hardware, system software, and/or applications, this paper explores approaches for quantifying the effects of prediction and mitigation strategies and demonstrates these using actual production system data. We describe context-relevant methodologies for determining themore » accuracy and cost-benefit of predictors. While many research studies have quantified the expected impact of growing system size, and the associated shortened mean time to failure (MTTF), on application performance in large-scale high-performance computing (HPC) platforms, there has been little if any work to quantify the possible gains from predicting system resource failures with significant but imperfect accuracy. This possibly stems from HPC system complexity and the fact that, to date, no one has established any good predictors of failure in these systems. Our work in the OVIS project aims to discover these predictors via a variety of data collection techniques and statistical analysis methods that yield probabilistic predictions. The question then is, 'How good or useful are these predictions?' We investigate methods for answering this question in a general setting, and illustrate them using a specific failure predictor discovered on a production system at Sandia.« less

Dipeptidyl peptidase-4 inhibitors and risk of heart failure in type 2 diabetes: systematic review and meta-analysis of randomised and observational studies.

PubMed

Li, Ling; Li, Sheyu; Deng, Ke; Liu, Jiali; Vandvik, Per Olav; Zhao, Pujing; Zhang, Longhao; Shen, Jiantong; Bala, Malgorzata M; Sohani, Zahra N; Wong, Evelyn; Busse, Jason W; Ebrahim, Shanil; Malaga, German; Rios, Lorena P; Wang, Yingqiang; Chen, Qunfei; Guyatt, Gordon H; Sun, Xin

2016-02-17

To examine the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and the risk of heart failure or hospital admission for heart failure in patients with type 2 diabetes. Systematic review and meta-analysis of randomised and observational studies. Medline, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov searched up to 25 June 2015, and communication with experts. Randomised controlled trials, non-randomised controlled trials, cohort studies, and case-control studies that compared DPP-4 inhibitors against placebo, lifestyle modification, or active antidiabetic drugs in adults with type 2 diabetes, and explicitly reported the outcome of heart failure or hospital admission for heart failure. Teams of paired reviewers independently screened for eligible studies, assessed risk of bias, and extracted data using standardised, pilot tested forms. Data from trials and observational studies were pooled separately; quality of evidence was assessed by the GRADE approach. Eligible studies included 43 trials (n=68,775) and 12 observational studies (nine cohort studies, three nested case-control studies; n=1,777,358). Pooling of 38 trials reporting heart failure provided low quality evidence for a possible similar risk of heart failure between DPP-4 inhibitor use versus control (42/15,701 v 33/12,591; odds ratio 0.97 (95% confidence interval 0.61 to 1.56); risk difference 2 fewer (19 fewer to 28 more) events per 1000 patients with type 2 diabetes over five years). The observational studies provided effect estimates generally consistent with trial findings, but with very low quality evidence. Pooling of the five trials reporting admission for heart failure provided moderate quality evidence for an increased risk in patients treated with DPP-4 inhibitors versus control (622/18,554 v 552/18,474; 1.13 (1.00 to 1.26); 8 more (0 more to 16 more)). The pooling of adjusted estimates from observational studies similarly suggested (with very low quality evidence) a possible increased risk of admission for heart failure (adjusted odds ratio 1.41, 95% confidence interval 0.95 to 2.09) in patients treated with DPP-4 inhibitors (exclusively sitagliptin) versus no use. The relative effect of DPP-4 inhibitors on the risk of heart failure in patients with type 2 diabetes is uncertain, given the relatively short follow-up and low quality of evidence. Both randomised controlled trials and observational studies, however, suggest that these drugs may increase the risk of hospital admission for heart failure in those patients with existing cardiovascular diseases or multiple risk factors for vascular diseases, compared with no use. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Effect of system workload on operating system reliability - A study on IBM 3081

NASA Technical Reports Server (NTRS)

Iyer, R. K.; Rossetti, D. J.

1985-01-01

This paper presents an analysis of operating system failures on an IBM 3081 running VM/SP. Three broad categories of software failures are found: error handling, program control or logic, and hardware related; it is found that more than 25 percent of software failures occur in the hardware/software interface. Measurements show that results on software reliability cannot be considered representative unless the system workload is taken into account. The overall CPU execution rate, although measured to be close to 100 percent most of the time, is not found to correlate strongly with the occurrence of failures. Possible reasons for the observed workload failure dependency, based on detailed investigations of the failure data, are discussed.

Revisiting the role of durable polymers in cardiovascular devices.

PubMed

Mori, Hiroyoshi; Otsuka, Fumiyuki; Gupta, Anuj; Jinnouchi, Hiroyuki; Torii, Sho; Harari, Emanuel; Virmani, Renu; Finn, Aloke V

2017-11-01

Polymers are an essential component of drug-eluting stents (DES) used to control drug release but remain the most controversial component of DES technology. There are two types of polymers employed in DES: durable polymer based DES (DP-DES) and biodegradable polymer DES (BP-DES). First-generation DES were exclusively composed of DP and demonstrated increased rates of late stent failure due in part to poor polymer biocompatibility. Newer generations DES use more biocompatible durable polymers or biodegradable polymers. Areas covered: We will cover issues identified with 1st-generation DP-DES, areas of success and failure in 2nd-generation DP-DES and examine the promise and shortcomings of BP-DES. Briefly, fluorinated polymers used in 2nd-generation DP-DES have excellent anti-thrombogenicity and better biocompatibility than 1st-generation DES polymers. However, these devices lead to persistent drug exposure to the endothelium which impairs endothelial function and predisposes towards neoatherosclerosis. Meanwhile, BP-DES has shortened the duration of drug exposure which might be beneficial for endothelial functional recovery leading to less neoatherosclerosis. However, it remains uncertain whether the long-term biocompatibility of bare metal surfaces is better than that of polymer-coated metals. Expert commentary: Each technology has distinct advantages, which can be optimized depending upon the particular characteristics of the patient being treated.

Ice-Cliff Failure via Retrogressive Slumping

NASA Astrophysics Data System (ADS)

Parizek, B. R.; Christianson, K.; Alley, R. B.; Voytenko, D.; Vankova, I.; Dixon, T. H.; Holland, D.

2016-12-01

The magnitude and rate of future sea-level rise from warming-induced ice-sheet shrinkage remain notably uncertain. Removal of most of an ice sheet by surface melting alone requires centuries to millennia. Oceanic warming may accelerate loss by removing buttressing ice shelves and thereby speeding flow of non-floating ice into the ocean, but, until recently, modeled timescales for major dynamic ice-sheet shrinkage were centuries or longer. Beyond certain thresholds, however, observations show that warming removes floating ice shelves, leaving grounded ice cliffs from which icebergs break off directly. Cliffs higher than some limit experience rapid structural failure. Recent parameterization of this process in a comprehensive ice-flow model produced much faster sea-level rise from future rapid warming than in previous modeling studies, through formation and retreat of tall ice cliffs. Fully physical representations of this process are not yet available, however. Here, we use modeling guided by terrestrial radar data from Helheim Glacier, Greenland to show that cliffs will fail by slumping and trigger rapid retreat at a threshold height that, in crevassed ice with surface melting, may be only slightly above the 100-m maximum observed today, but may be roughly twice that (180-275 m) in mechanically-competent ice under well-drained or low-melt conditions.

Resistance to echinocandin-class antifungal drugs

PubMed Central

Perlin, David S.

2009-01-01

Invasive fungal infections cause morbidity and mortality in severely ill patients, and limited drug classes restrict treatment choices. The echinocandins drugs are the first new class of antifungal compounds that target the fungal cell wall by blocking β-1,3-D-glucan synthase. Elevated MIC values with occasional treatment failure have been reported for strains of Candida. Yet, an uncertain correlation exists between clinical failure and elevated MIC values for the echinocandin drugs. Fungi display several adaptive physiological mechanisms that result in elevated MIC values. However, resistance to echinocandin drugs among clinical isolates is associated with amino acid substitutions in two “hot-spot” regions of Fks1, the major subunit of glucan synthase. The mutations, yielding highly elevated MIC values, are genetically dominant and confer cross-resistance to all echinocandin drugs. Prominent Fks1 mutations decrease the sensitivity of glucan synthase for drug by one thousand-fold or more, and strains harboring such mutations may require a concomitant increase in drug to reduce fungal organ burdens in animal infection models. The Fks1-mediated resistance mechanism is conserved in a wide variety of Candida spp. and can account for intrinsic reduced susceptibility of certain species. Fks1 mutations confer resistance in both yeasts and moulds suggesting that this mechanism is pervasive in the fungal kingdom. PMID:17569573

Viral blips during suppressive antiretroviral treatment are associated with high baseline HIV-1 RNA levels.

PubMed

Sörstedt, Erik; Nilsson, Staffan; Blaxhult, Anders; Gisslén, Magnus; Flamholc, Leo; Sönnerborg, Anders; Yilmaz, Aylin

2016-06-21

Many HIV-1-infected patients on suppressive antiretroviral therapy (ART) have transiently elevated HIV RNA levels. The clinical significance of these viral blips is uncertain. We have determined the incidence of blips and investigated important associations in the Swedish HIV-cohort. HIV-1-infected ART naïve adults who commenced ART 2007-2013 were retrospectively included. Viral blips were defined as a transient viral load between 50 and 500 copies/mL Subjects not suppressed after six months on ART were excluded. Viral blips were found in 76/735 included subjects (10.3 %) and in 90/4449 samples (2.0 %). Median blip viral load was 76 copies/mL (range 56-138). Median follow-up time was 170 weeks (range 97-240). Baseline viral load was higher in subjects with viral blips (median log10 4.85 copies/mL) compared with subjects without blips (median log10 4.55 copies/mL) (p < 0.01). There was a significant association between viral blips and risk for subsequent virological failure (p < 0.001). The Swedish national HIV-cohort has a low incidence of viral blips (10 %). Blips were associated with high baseline viral load and an increased risk of subsequent virological failure.

Weight-of-evidence evaluation of an adverse outcome ...

EPA Pesticide Factsheets

Ongoing honey bee colony losses are of significant international concern because of the essential role these insects play in pollinating staple food crops. Chemical and non-chemical stressors both have been implicated as possible contributors to colony failure, however, the potential role of commonly-used neonicotinoid insecticides has emerged as particularly concerning. Neonicotinoids act on the nicotinic acetylcholine receptor (nAChR) to eliminate target pest insects, however, mounting evidence indicates that these chemicals may adversely affect beneficial pollinators, such as the honey bee, via impacts on learning and memory thereby affecting foraging success. However, the mechanisms linking activation of the nAChR to adverse effects on learning and memory are uncertain. Additionally, clear connections between observed impacts on individual bees and colony level effects are lacking. Therefore, the objective of this work was to develop adverse outcome pathways (AOPs) as a means to evaluate the biological plausibility and empirical evidence supporting (or refuting) the linkage between the nAChR and colony level impacts. Development of these AOPs has led to the identification of research gaps which, for example, may be of high priority in understanding how perturbation of pathways involved in neurotransmission can adversely affect honey bee health, causing colony instability and further failure. From this effort, an AOP network also was developed, laying the f

Asteroid diversion considerations and comparisons of diversion techniques

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

Owen, J. Michael; Miller, Paul; Rovny, Jared

The threat of asteroid impacts on Earth poses a low-probability but high consequence risk, with possible outcomes ranging from regional to global catastrophe. However, unique amongst such global threats we have the capability of averting such disasters. Diversion approaches by either kinetic impactor or nuclear energy deposition are the two most practical technologies for mitigating hazardous near Earth asteroids. One of the greatest challenges in understanding our options is the uncertain response of asteroids to such impulsive techniques, due both to our lack of knowledge of the composition and structure of these objects as well as their highly varied nature.more » Predicting whether we will simply divert or break up a given object is a crucial: the weak self-gravity and inferred weak structure of typical asteroids present the strong possibility the body will fragment for modest impulses. Predictive modeling of failure and fragmentation is one important tool for such studies. In this paper we apply advances in modeling failure and fracture using Adaptive Smoothed Particle Hydrodynamics (ASPH) to understand mega-cratering on asteroids as a validation exercise, and show examples of diverting the near Earth asteroid Bennu using both a kinetic impactor and ablative blow-off due to nuclear energy deposition.« less

Asteroid diversion considerations and comparisons of diversion techniques

DOE PAGES

Owen, J. Michael; Miller, Paul; Rovny, Jared; ...

2015-05-19

The threat of asteroid impacts on Earth poses a low-probability but high consequence risk, with possible outcomes ranging from regional to global catastrophe. However, unique amongst such global threats we have the capability of averting such disasters. Diversion approaches by either kinetic impactor or nuclear energy deposition are the two most practical technologies for mitigating hazardous near Earth asteroids. One of the greatest challenges in understanding our options is the uncertain response of asteroids to such impulsive techniques, due both to our lack of knowledge of the composition and structure of these objects as well as their highly varied nature.more » Predicting whether we will simply divert or break up a given object is a crucial: the weak self-gravity and inferred weak structure of typical asteroids present the strong possibility the body will fragment for modest impulses. Predictive modeling of failure and fragmentation is one important tool for such studies. In this paper we apply advances in modeling failure and fracture using Adaptive Smoothed Particle Hydrodynamics (ASPH) to understand mega-cratering on asteroids as a validation exercise, and show examples of diverting the near Earth asteroid Bennu using both a kinetic impactor and ablative blow-off due to nuclear energy deposition.« less

Exploring gay couples' experience with sexual dysfunction after radical prostatectomy: a qualitative study.

PubMed

Hartman, Mary-Ellen; Irvine, Jane; Currie, Kristen L; Ritvo, Paul; Trachtenberg, Lianne; Louis, Alyssa; Trachtenberg, John; Jamnicky, Leah; Matthew, Andrew G

2014-01-01

This exploratory study examines the experience of three gay couples managing sexual dysfunction as a result of undergoing a radical prostatectomy. Semi-structured interviews were conducted as part of a larger study at an urban hospital in Toronto, Ontario, Canada. Interview transcripts were transcribed verbatim, and analyzed using interpretative phenomenological analysis. The authors clustered 18 subordinate themes under 3 superordinate themes: (a) acknowledging change in sexual experience (libido, erectile function, sexual activity, orgasmic function); (b) accommodating change in sexual experience (strategies: emphasizing intimacy, embracing plan B, focus on the other; barriers: side-effect concerns, loss of naturalness, communication breakdown, failure to initiate, trial and failure, partner confounds); and (c) accepting change in sexual experience (indicators: emphasizing health, age attributions, finding a new normal; barriers: uncertain outcomes, treatment regrets). Although gay couples and heterosexual couples share many similar challenges, we discovered that gay men have particular sexual roles and can engage in novel accommodation practices, such as open relationships, that have not been noted in heterosexual couples. All couples, regardless of their level of sexual functioning, highlighted the need for more extensive programming related to sexual rehabilitation. Equitable rehabilitative support is critical to assist homosexual couples manage distress associated with prostatectomy-related sexual dysfunction.

A systems engineering approach to automated failure cause diagnosis in space power systems

NASA Technical Reports Server (NTRS)

Dolce, James L.; Faymon, Karl A.

1987-01-01

Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.

Degenerative disease affecting the nervous system.

PubMed

Eadie, M J

1974-03-01

The term "degenerative disease" is one which is rather widely used in relation to the nervous system and yet one which is rarely formally and carefully defined. The term appears to be applied to disorders of the nervous system which often occur in later life and which are of uncertain cause. In the Shorter Oxford Dictionary the word degeneration is defined as "a change of structure by which an organism, or an organ, assumes the form of a lower type". However this is not quite the sense in which the word is applied in human neuropathology, where it is conventional to restrict the use of the word to those organic disorders which are of uncertain or poorly understood cause and in which there is a deterioration or regression in the level of functioning of the nervous system. The concept of degenerative disorder is applied to other organs as well as to the brain, and as disease elsewhere in the body may affect the nervous system, it seems reasonable to include within the topic of degenerative disorder affecting the nervous system those conditions in which the nervous system is involved as a result of primary degenerations in other parts of the body. Copyright © 1974 Australian Physiotherapy Association. Published by . All rights reserved.

Development System for Flexible Assembly System.

DTIC Science & Technology

1986-02-01

in( tho .Iho Iacli: that is, the estimated so’arae hows extrene senisitivity t Ihe t’rr ,f ,rii It: input angles in the vacinity of a pole. These...investigating is to prerotate the world frame so that none of the uncertain transformations have nominal angles in the vacinity of a pole. 17 %% ’ ,’f

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

A high-angle-of-attack flush airdata sensing system was installed and flight tested on the F-18 High Alpha Research Vehicle at NASA-Dryden. This system uses a matrix of pressure orifices arranged in concentric circles on the nose of the vehicle to determine angles of attack, angles of sideslip, dynamic pressure, and static pressure as well as other airdata parameters. Results presented use an arrangement of 11 symmetrically distributed ports on the aircraft nose. Experience with this sensing system data indicates that the primary concern for real-time implementation is the detection and management of overall system and individual pressure sensor failures. The multiple port sensing system is more tolerant to small disturbances in the measured pressure data than conventional probe-based intrusive airdata systems. However, under adverse circumstances, large undetected failures in individual pressure ports can result in algorithm divergence and catastrophic failure of the entire system. How system and individual port failures may be detected using chi sq. analysis is shown. Once identified, the effects of failures are eliminated using weighted least squares.

A novel medical information management and decision model for uncertain demand optimization.

PubMed

Bi, Ya

2015-01-01

Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.

Failure Mode, Effects, and Criticality Analysis (FMECA)

DTIC Science & Technology

1993-04-01

Preliminary Failure Modes, Effects and Criticality Analysis (FMECA) of the Brayton Isotope Power System Ground Demonstration System, Report No. TID 27301...No. TID/SNA - 3015, Aeroject Nuclear Systems Co., Sacramento, California: 1970. 95. Taylor , J.R. A Formalization of Failure Mode Analysis of Control...Roskilde, Denmark: 1973. 96. Taylor , J.R. A Semi-Automatic Method for Oualitative Failure Mode Analysis. Report No. RISO-M-1707. Available from a

10 CFR 1008.24 - Criminal penalties-failure to publish a system notice.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 4 2010-01-01 2010-01-01 false Criminal penalties-failure to publish a system notice...—failure to publish a system notice. Subsection (i)(2) of the Act provides that an agency officer or employee who willfully maintains a system of records without publishing a system notice as required by...

Common Cause Failure Modeling: Aerospace Versus Nuclear

NASA Technical Reports Server (NTRS)

Stott, James E.; Britton, Paul; Ring, Robert W.; Hark, Frank; Hatfield, G. Spencer

2010-01-01

Aggregate nuclear plant failure data is used to produce generic common-cause factors that are specifically for use in the common-cause failure models of NUREG/CR-5485. Furthermore, the models presented in NUREG/CR-5485 are specifically designed to incorporate two significantly distinct assumptions about the methods of surveillance testing from whence this aggregate failure data came. What are the implications of using these NUREG generic factors to model the common-cause failures of aerospace systems? Herein, the implications of using the NUREG generic factors in the modeling of aerospace systems are investigated in detail and strong recommendations for modeling the common-cause failures of aerospace systems are given.

Software For Fault-Tree Diagnosis Of A System

NASA Technical Reports Server (NTRS)

Iverson, Dave; Patterson-Hine, Ann; Liao, Jack

1993-01-01

Fault Tree Diagnosis System (FTDS) computer program is automated-diagnostic-system program identifying likely causes of specified failure on basis of information represented in system-reliability mathematical models known as fault trees. Is modified implementation of failure-cause-identification phase of Narayanan's and Viswanadham's methodology for acquisition of knowledge and reasoning in analyzing failures of systems. Knowledge base of if/then rules replaced with object-oriented fault-tree representation. Enhancement yields more-efficient identification of causes of failures and enables dynamic updating of knowledge base. Written in C language, C++, and Common LISP.

Altered subjective reward valuation among female heavy marijuana users.

PubMed

Hefner, Kathryn R; Starr, Mark J

2017-02-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, Marijuana Group and Sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of Sex differed by Marijuana Group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the "stakes" were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users' sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users' sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Altered subjective reward valuation among female heavy marijuana users

PubMed Central

Hefner, Kathryn R.; Starr, Mark. J.

2016-01-01

Maladaptive decision-making is a cardinal feature of drug use, contributing to ongoing use, and reflecting alterations in how drug users assess uncertain reward value. Accumulating evidence indicates the consequences of heavy marijuana use are worse for female versus male animals and humans, but research assessing sex differences in reward-related decision-making among marijuana users remains scarce. We examined sex differences in the subjective valuation of certain and uncertain rewards among heavy marijuana users (52; 26 male and 26 female) and controls (52; 26 male and 26 female). We offered male and female heavy marijuana users and controls monetary rewards of certain and uncertain (probabilistic) values. We measured how preferences for uncertain rewards varied by the objective value of those rewards, moderators of reward uncertainty, marijuana use, and sex. Men were more sensitive to changes in the objective value of uncertain rewards than women. However, this effect of sex differed by marijuana group. Female heavy marijuana users were more sensitive to changes in uncertain reward value, particularly when the ‘stakes’ were high (i.e., greater difference between potential uncertain rewards), than female controls. Female heavy marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards was comparable to male marijuana users and controls. In contrast, male marijuana users’ sensitivity to changes in the value of high stakes uncertain rewards did not differ from male controls. These results suggest sex differences in sensitivity to high risk rewards may be one pathway contributing to severer consequences of heavy marijuana use among women. PMID:27936816

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

Sensor failure and multivariable control for airbreathing propulsion systems. Ph.D. Thesis - Dec. 1979 Final Report

NASA Technical Reports Server (NTRS)

Behbehani, K.

1980-01-01

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Risk assessment for enterprise resource planning (ERP) system implementations: a fault tree analysis approach

NASA Astrophysics Data System (ADS)

Zeng, Yajun; Skibniewski, Miroslaw J.

2013-08-01

Enterprise resource planning (ERP) system implementations are often characterised with large capital outlay, long implementation duration, and high risk of failure. In order to avoid ERP implementation failure and realise the benefits of the system, sound risk management is the key. This paper proposes a probabilistic risk assessment approach for ERP system implementation projects based on fault tree analysis, which models the relationship between ERP system components and specific risk factors. Unlike traditional risk management approaches that have been mostly focused on meeting project budget and schedule objectives, the proposed approach intends to address the risks that may cause ERP system usage failure. The approach can be used to identify the root causes of ERP system implementation usage failure and quantify the impact of critical component failures or critical risk events in the implementation process.

Reliable Control Using Disturbance Observer and Equivalent Transfer Function for Position Servo System in Current Feedback Loop Failure

NASA Astrophysics Data System (ADS)

Ishikawa, Kaoru; Nakamura, Taro; Osumi, Hisashi

A reliable control method is proposed for multiple loop control system. After a feedback loop failure, such as case of the sensor break down, the control system becomes unstable and has a big fluctuation even if it has a disturbance observer. To cope with this problem, the proposed method uses an equivalent transfer function (ETF) as active redundancy compensation after the loop failure. The ETF is designed so that it does not change the transfer function of the whole system before and after the loop failure. In this paper, the characteristic of reliable control system that uses an ETF and a disturbance observer is examined by the experiment that uses the DC servo motor for the current feedback loop failure in the position servo system.

Deduction with Uncertain Conditionals

DTIC Science & Technology

2002-04-01

operations but a very different fourth operation, again meant as an implication. As mentioned by Gilio and Scozzafava [19], in 1985 Bruno and Gilio also...nonmonotonic consequence relationships, IEEE Transactions of Systems, Man and Cybernetics 24 (12) (1994) 1724-1740. [19] A. Gilio , R. Scozzafava