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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

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↗

Chemistry in CESM-SE: Evaluation, Performance and Optimization

The purpose of the proposed work focused on development of chemistry representation within the Spectral Element (SE) dynamical core as implemented in the Community Earth System Model (CESM). More specifically, a main focus was on the ability of SE to accurately represent tracer transport. The proposed approach was to incrementally increase the complexity of the problem, starting from specified two-dimensional flow and tracers to simulations using specified dynamics and full chemistry. As demonstrated below, we have successfully studied all aspects of the proposed work, although only part of the work has been published in the refereed literature so far. Furthermore, because the SE dynamical core has been found to have several deficiencies that are still being investigated for solution, not all proposed tasks were finalized. In addition to the tests for SE performance, in an effort to decrease the computational burden of interactive chemistry, especially in the case of a large number of chemical species and chemical reactions, development on a faster chemical solver and implementation on GPUs has been implemented in CESM under the leadership of John Drake (U. Tennessee).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Doping CdSexTe1-x/CdTe Graded Absorber Films with Arsenic for Thin-Film Photovoltaics

CdTe thin-film photovoltaics have demonstrated some of the lowest costs of electricity generation owing to its low material cost and ease of manufacturing. However, the full potential of polycrystalline CdTe photovoltaics can only be realized if the open-circuit voltage can be increased beyond 1 V Open-circuit voltage ~850-900 mV has been consistently observed for state-of-the-art polycrystalline CdTe solar cells. Open-circuit voltage of over 1V has been demonstrated for single crystal CdTe devices by doping with Group V elements. Therefore, this study is aimed at understanding behavior of polycrystalline CdTe devices with arsenic doping, its activation and process and performance optimization in order to overcome current voltage limitations in CdTe solar cells.

14 SOLAR ENERGY↗

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.↗

Re-Engineering Poly(Acrylic Acid) Binder toward Optimized Electrochemical Performance for Silicon Lithium-Ion Batteries: Branching Architecture Leads to Balanced Properties of Polymeric Binders

Silicon is a promising anode material for lithium-ion batteries with its superior capacity. However, the drastic volume changes during lithiation/delithiation cycles hinder the cycling performance, resulting in particle pulverization, conductivity loss, and an unstable electrode-electrolyte interface. In this work, a series of synthetic polymeric binders, poly(acrylic acid-co-tetra(ethylene glycol) diacrylate)-featuring a poly(acrylic acid) (PAA) backbone branched via tetra(ethylene glycol) diacrylate (TEGDA)-are developed that edge toward evidencing well-balanced properties to confront capacity fading in Si-based electrodes. The incorporation of ether chain not only leads to the branching architecture of the PAA backbone, thus affecting its mechanical properties, but also promotes the conductivity of Li ions. As a result, a synergistic performance improvement is observed in both half and full cells. The best-performing cell using a branched PAA binder (bPAA) with a feeding molar ratio ([TEGDA]:[acrylic acid(AA)]) of 0.2 results in a 10% increase in initial capacity and a 31% increase in capacity retention over 100 cycles compared to the linear PAA cell. The cross-sectional microscopic images of the cycled electrodes reveal that bPAA binders can drastically reduce the electrode expansion. This improvement results from the well-balanced properties of the polymer design, which could guide further development for more advanced binder materials.

25 ENERGY STORAGE↗

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

Scientific data analytics in high-performance computing environments has been evolving along with the advancement of computing capabilities. With the onset of exascale computing, the increasing gap between compute performance and I/O bandwidth has rendered the traditional post-simulation processing a tedious process. Despite the challenges due to increased data production, there exists an opportunity to benefit from "cheap" computing power to perform query-driven exploration and visualization during simulation time. To accelerate such analyses, applications traditionally augment, post-simulation, raw data with large indexes, which are then repeatedly utilized for data exploration. However, the generation of current state-of-the-art indexes involves a compute- and memory-intensive processing, thus rendering them inapplicable in an in situ context. In this paper we propose DIRAQ, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. DIRAQ's effective core-local, precision-based encoding approach incorporates an embedded compressed index that is 3---6 $$\times $$ ? smaller than current state-of-the-art indexing schemes. Its data-aware index adjustmentation improves performance of group-level index layout creation by up to 35 % and reduces the size of the generated index by up to 27 %. Moreover, DIRAQ's in network index merging strategy enables the creation of aggregated indexes that speed up spatial-context query responses by up to $$10\times $$ 10 ? versus alternative techniques. DIRAQ's topology-, data-, and memory-aware aggregation strategy results in efficient I/O and yields overall end-to-end encoding and I/O time that is less than that required to write the raw data with MPI collective I/O.

Computer Science↗

Evaluating adaptive and predictive power management strategies for optimizing visualization performance on supercomputers

Power is becoming an increasingly scarce resource on the next generation of supercomputers, and should be used wisely to improve overall performance. One strategy for improving power usage is hardware overprovisioning, i.e., systems with more nodes than can be run at full power simultaneously without exceeding the system-wide power limit. With this study, we compare two strategies for allocating power throughout an overprovisioned system – adaptation and prediction – in the context of visualization workloads. While adaptation has been suitable for workloads with more regular execution behaviors, it may not be as suitable on visualization workloads, since they can have variable execution behaviors. This study considers a total of 104 experiments, which vary the rendering workload, power budget, allocation strategy, and node concurrency, including tests processing data sets up to 1 billion cells and using up to 18,432 cores across 512 nodes. Overall, we find that prediction is a superior strategy for this use case, improving performance up to 27% compared to an adaptive strategy.

97 MATHEMATICS AND COMPUTING↗

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↗