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At least 181 records · Page 10

Agent Reward Shaping for Alleviating Traffic Congestion

Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

Tumer, Kagan

Parametric study of critical constraints for a canard configured medium range transport using conceptual design optimization

Constrained parameter optimization was used to perform optimal conceptual design of both canard and conventional configurations of a medium range transport. A number of design constants and design constraints were systematically varied to compare the sensitivities of canard and conventional configurations to a variety of technology assumptions. Main landing gear location and horizontal stabilizer high-lift performance were identified as critical design parameters for a statically stable, subsonic canard transport.

Arbuckle, P. D.

Parametric study of a canard-configured transport using conceptual design optimization

Constrained-parameter optimization is used to perform optimal conceptual design of both canard and conventional configurations of a medium-range transport. A number of design constants and design constraints are systematically varied to compare the sensitivities of canard and conventional configurations to a variety of technology assumptions. Main-landing-gear location and canard surface high-lift performance are identified as critical design parameters for a statically stable, subsonic, canard-configured transport.

Arbuckle, P. D.

Etching-Chemistry-Driven Ruthenium Doping on Ti 3 C 2 T x MXene for Optimizing Electrochemical Performance

We demonstrate that the etching chemistry used during MXene synthesis from Ti 3 AlC 2 MAX phase significantly influences surface functionalization and structural vacancies, which in turn affect ruthenium (Ru) ion interactions. Using hydrofluoric acid (HF) and ammonium bifluoride (NH 4 HF 2 ) as etchants, we obtained MXene surfaces with distinct functional groups and Ti vacancies that impact Ru ion interactions and electrochemical performance. Both MXene variants (labeled MX(H) and MX(N), respectively) exhibited negative zeta potentials in their pristine state, but upon the addition of Ru the zeta potential for MX(H) reached 12.9 mV while that for MX(N) remained negative at −6.4 mV. This adsorption resulted in a 14.4-fold increase in the specific capacitance of MX(H)/Ru compared to pristine MX(H), whereas MX(N)/Ru exhibited only a 4.4-fold increase over its pristine counterpart. X-ray diffraction analysis identified the formation of ammonium titanium oxide fluoride, (NH 4 ) 3 TiOF 5 , on MX(N), which likely contributed to its reduced Ru adsorption. X-ray photoelectron spectroscopy suggested the presence of Ti vacancies in both MXene variants; however, their behavior toward Ru accommodation differed markedly, with MX(H) showing the most obvious shift in the Ti 2p peak in the XPS survey spectrum, while MX(N) showed the most obvious shift in the C 1s peak. Electron paramagnetic resonance spectroscopy further demonstrated a distinct alteration in the spectral signatures of MX(H) upon Ru addition, in contrast to the negligible changes in MX(N), indicating effective passivation of the Ti defect sites in MX(H) via vacancy-assisted Ru doping. Cyclic voltammetry showed that Ru-incorporated MX(H) nanocomposites exhibit more efficient redox-active sites, as reflected in their higher capacitance values. These findings highlight the pivotal role of MXene surface chemistry in controlling cation adsorption, providing valuable insights for the rational design of high-performance electrodes.

2D surface engineering

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network

Insights from Optimizing HPL Performance on Exascale Systems: A Comparative Analysis of Panel Factorization

High performance LINPACK (HPL) remains the primary benchmark for evaluating supercomputing performance. It includes many parts with substantial internal complexity, and its performance is affected by a large number of parameters that interact in ways that are difficult to predict on large-scale heterogeneous supercomputer systems. We present a comprehensive performance analysis of HPL on Frontier, the world’s first exascale supercomputer, which achieved HPL performance of 1.35 exaflops. Through empirical parameter tuning, detailed modeling, and comparative evaluation, we uncover critical performance insights, share lessons learned, and outline best practices for effective parameter tuning on exascale systems. We introduce and evaluate two novel PDFACT strategies: a dedicated-thread (DT) variant and a GPU-based variant (GPUPDFACT) implementation using HIP cooperative groups, demonstrating that GPU-based factorization outperforms conventional CPU-based PDFACT on Frontier’s architecture. Our findings establish key performance factors for HPL on exascale systems and offer valuable guidance for future high-performance computing and benchmarking efforts.

Lu, Hao [ORNL] (ORCID:000000018941870X)

Development of management technology for large power systems

Autonomous power management has been proposed as a method to perform optimization of power subsystem performance in connection with the management of multikilowatt space platforms. A concept for a 250-kW utility-type power subsystem was developed. A Cassegrain concentrator solar array primary source is conditioned by a solar array switching unit which supplies seventeen 220 +20 Vdc power channels. A power management subsystem provides the monitoring and control of the overall electrical power subsystem. The discussed system concept for autonomous management of high power space platforms utilizes on-board microprocessors in a decentralized data management architecture. A data bus protocol and a data bus contention resolution scheme were selected in conjunction with the dencentralized management architecture.

Decker, D. K.

Selection for optimal crew performance - Relative impact of selection and training

An empirical study supporting Helmreich's (1986) theoretical work on the distinct manner in which training and selection impact crew coordination is presented. Training is capable of changing attitudes, while selection screens for stable personality characteristics. Training appears least effective for leadership, an area strongly influenced by personality. Selection is least effective for influencing attitudes about personal vulnerability to stress, which appear to be trained in resource management programs. Because personality correlates with attitudes before and after training, it is felt that selection may be necessary even with a leadership-oriented training cirriculum.

Chidester, Thomas R.

Optimizing raid performance with cache

We live in a world of increasingly complex applications and operating systems. Information is increasing at a mind-boggling rate. The consolidation of text, voice, and imaging represents an even greater challenge for our information systems. Which forced us to address three important questions: Where do we store all this information? How do we access it? And, how do we protect it against the threat of loss or damage? Introduced in the 1980s, RAID (Redundant Arrays of Independent Disks) represents a cost-effective solution to the needs of the information age. While fulfilling expectations for high storage, and reliability, RAID is sometimes subject to criticisms in the area of performance. However, there are design elements that can significantly enhance performance. They can be subdivided into two areas: (1) RAID levels or basic architecture. And, (2) enhancement schemes such as intelligent caching, support of tagged command queuing, and use of SCSI-2 Fast and Wide features.

Bouzari, Alex

The Efficiency of Various Computers and Optimizations in Performing Finite Element Computations

With the advent of computers with many processors, it becomes unclear how to best exploit this advantage. For example, matrices can be inverted by applying several processors to each vector operation, or one processor can be applied to each matrix. The former approach has diminishing returns beyond a handful of processors, but how many processors depends on the computer architecture. Applying one processor to each matrix is feasible with enough ram memory and scratch disk space, but the speed at which this is done is found to vary by a factor of three depending on how it is done. The cost of the computer must also be taken into account. A computer with many processors and fast interprocessor communication is much more expensive than the same computer and processors with slow interprocessor communication. Consequently, for problems that require several matrices to be inverted, the best speed per dollar for computers is found to be several small workstations that are networked together, such as in a Beowulf cluster. Since these machines typically have two processors per node, each matrix is most efficiently inverted with no more than two processors assigned to it.

Marcus, Martin H.

Particle Swarm Optimization

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

Venter, Gerhard

Bioastronautics: optimizing human performance through research and medical innovations

A strategic use of resources is essential to achieving long-duration space travel and understanding the human physiological changes in space, including the roles of food and nutrition in space. To effectively address the challenges of space flight, the Bioastronautics Initiative, undertaken in 2001, expands extramural collaboration and leverages unique capabilities of the scientific community and the federal government, all the while applying this integrated knowledge to Earth-based problems. Integral to the National Aeronautics and Space Administration's missions in space is the reduction of risk of medical complications, particularly during missions of long duration. Cumulative medical experience and research provide the ability to develop evidence-based medicine for prevention, countermeasures, and treatment modalities for space flight. The early approach applied terrestrial clinical judgment to predict medical problems in space. Space medicine has evolved to an evidence-based approach with the use of biomedical data gathered and lessons learned from previous space flight missions to systematically aid in decision making. This approach led, for example, to the determination of preliminary nutritional requirements for space flight, and it aids in the development of nutrition itself as a countermeasure to support nutritional mitigation of adaptation to space.

Nutritional Requirements

Performance and optimization of a combustion interface for isotope ratio monitoring gas chromatography/mass spectrometry

Conditions and systems for on-line combustion of effluents from capillary gas chromatographic columns and for removal of water vapor from product streams were tested. Organic carbon in gas chromatographic peaks 15 s wide and containing up to 30 nanomoles of carbon was quantitatively converted to CO2 by tubular combustion reactors, 200 x 0.5 mm, packed with CuO or NiO. No auxiliary source of O2 was required because oxygen was supplied by metal oxides. Spontaneous degradation of CuO limited the life of CuO reactors at T > 850 degrees C. Since NiO does not spontaneously degrade, its use might be favored, but Ni-bound carbon phases form and lead to inaccurate isotopic results at T < 1050 degrees C if gas-phase O2 is not added. For all compounds tested except CH4, equivalent isotopic results are provided by CuO at 850 degrees C, NiO + O2 (gas-phase mole fraction, 10(-3)) at 1050 degrees C and NiO at 1150 degrees C. The combustion interface did not contribute additional analytical uncertainty, thus observed standard deviations of 13C/12C ratios were within a factor of 2 of shot-noise limits. For combustion and isotopic analyses of CH4, in which quantitative combustion required T approximately 950 degrees C, NiO-based systems are preferred, and precision is approximately 2 times lower than that observed for other analytes. Water must be removed from the gas stream transmitted to the mass spectrometer or else protonation of CO2 will lead to inaccuracy in isotopic analyses. Although thresholds for this effect vary between mass spectrometers, differential permeation of H2O through Nafion tubing was effective in both cases tested, but the required length of the Nafion membrane was 4 times greater for the more sensitive mass spectrometer.

NASA Discipline Exobiology

Considerations for Isochronous Data Services over the Proximity-1 Space Link

Future mission concepts for robotic and human explorations will involve a high level of real time control/monitoring operations such as tele-operation for spacecraft rendezvous and surface mobile platforms carrying life-support equipments. The timely dissemination of voice, command, and real-time telemetry for monitoring and coordination purposes is critical for mission success. It is envisioned that future missions will require a network infrastructure capable of supporting isochronous data services. The CCSDS Proximity-1 Space Link Protocol1 could be used to provide isochronous service over the surface-to-Earth relay as well as "beyond-the-horizon" communications between distant Lunar or Mars surface elements. This paper will analyze the latency, jitter, and throughput performance of the Proximity-1 protocol for isochronous applications. In particular we will focus on constrained scenarios where the protocol operates in full-duplex mode, carrying isochronous traffic in one direction and error-controlled traffic in the other direction. We analyze the impact of the strict priority scheme in Proximity-1 on delay jitter and the impact of the isochronous traffic on the efficiency of the reliable data transfer in the other direction, and discuss methods for performance optimization. In general, jitter performance is driving by relative loading of isochronous traffic on the forward link compared to the acknowledgement traffic. Under light loading condition, the upper-bound of the delay jitter is the transmission duration of an acknowledgement frame on the forward link; for higher loading scenarios, the maximum jitter is scaled up by the inverse of the residual bandwidth, i.e., the spare capacity available in the forward link to carry isochronous traffic.

isochronous communications