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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 127 records · Page 7

Model Predictive Control-Based Trajectory Shaper for Safe and Efficient Adaptive Cruise Control

Recent studies show that commercially-available adaptive cruise control (ACC) systems are string-unstable, indicating that ACC-driven vehicles amplify speed fluctuations from downstream traffic and induce stop-and-go waves. Moreover, it is challenging to revise the original control algorithm of an ACC system to achieve string stability due to its internal complexity and powertrain uncertainties. To achieve desired control performance given a string-unstable ACC system and circumvent revising the original control algorithm, this study proposes a model predictive control-based trajectory shaper (MPC-TS), which only modifies the sensor-measured trajectory information (i.e., position and speed) of the preceding vehicle. The proposed MPC-TS leverages the input shaping technique to generate reference trajectory to improve string stability, while incorporating tracking errors and vehicle acceleration/deceleration magnitude in the MPC cost function and constraining fluctuations of vehicle speed and spacing to ensure desired car-following performance. Numerical experiments validate the control performance of ACC with the proposed MPC-TS in terms of string stability, safety, traffic efficiency, and comfort.

Zhou, Anye↗

Safe and Robust Binary Classification and Fault Detection Using Reinforcement Learning

In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to identify valid input spaces in high-dimensional, highly constrained systems while minimizing the total runtime of offline simulations. The simulations adapt their runtime based on the likelihood that a given training input will be informative to the classifier. Furthermore, we introduce a method for using the trained SAC model to predict whether a desired system input is likely to violate constraints, along with a technique to adjust the input as necessary. Additionally, we explore the potential of this model to detect faults or adversarial attacks within the system. The effectiveness of our approach is demonstrated through various simulations of challenging classification problems and a constrained quadrotor model.

Netter, Josh [Georgia Institute of Technology, Atl↗

Safe Exploration Reinforcement Learning for Load Restoration using Invalid Action Masking

This paper addresses the load restoration problem after a power outage event. Our primary proposed methodology uses a multi-agent reinforcement learning method to make the optimal sequential decisions on picking up critical loads. Typically, a negative reward is provided to discourage the agents from selecting decisions that violate physical constraints during the restoration process. However, the main disadvantage of this approach is its difficulty in applying it to large-scale systems due to the curse of dimensionality. This paper introduces the invalid action masking technique to overcome this limitation. The features of this technique include zero physical constraint violations, reduced training time, and stabilization of the explo- ration process. Simulation results are performed in IEEE 13-node and IEEE 123-node systems showing the better performance of the proposed algorithm in comparison to the conventional approaches both in terms of restored power and learning curve.

reinforcement learning, blackstart, artificial int↗

Dedicated short range communications used as fail-safe in autonomous navigation

Here in this paper, we have analyzed scenarios for leader-follower vehicle convoys that have the potential to be unsafe, hazardous, or even fatal in order to provide insight on dangerous driving conditions for autonomous vehicle platoons. These scenarios were created in a simulation software called Prescan, and are made to reflect the behavior of the vehicle dynamics and sensor characteristics of a real-world vehicle convoy that is currently being tested at the American Center for Mobility (ACM) and sponsored by the Department of Energy (DOE), National Renewable Energy Laboratory (NREL), the U.S. Army Combat Capabilities Development Command - Ground Vehicle Systems Center (U.S. Army CC-DEVCOM) and the Michigan Department of Transportation (MDOT). The follower vehicle in this study is tested under multiple scenarios, equipped with a Dedicated Short Range vehicle-to-vehicle communication system (DSRC), a radar-based adaptive cruise control system (ACC) and a precision global positioning system (GPS).

42 ENGINEERING↗

Liquid solution centrifugation for safe, scalable, and efficient isotope separation

A general method of separating isotopes by centrifuging dissolved chemical compounds in a liquid is introduced. This technique can be applied to almost all elements and leads to large separation factors. The method has been demonstrated in several isotopic systems including Ca, Mo, O, and Li with single-stage selectivities of 1.046 to 1.067 per neutron mass difference (e.g., 1.43 in 40 Ca/ 48 Ca), which are beyond the capabilities of various conventional methods. Equations are derived to model the process, and the results agree with those of the experiments. The scalability of the technique has been demonstrated by a three-stage enrichment of 48 Ca with a total 40 Ca/ 48 Ca selectivity of 2.43, and the scalability is more broadly supported through analogies to gas centrifuge, whereby countercurrent centrifugation can further multiply the separation factor by 5 to 10 times per stage in a continuous process. Optimal centrifuge conditions and solutions can achieve both high-throughput and highly efficient isotope separation.

07 ISOTOPE AND RADIATION SOURCES↗

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Safe Urban Harvests Study: A Community-Driven Cross-Sectional Assessment of Metals in Soil, Irrigation Water, and Produce from Urban Farms and Gardens in Baltimore, Maryland

BACKGROUND: Emerging evidence suggests social, health, environmental, and economic benefits of urban agriculture (UA). However, limited work has characterized the risks from metal contaminant exposures faced by urban growers and consumers of urban-grown produce. OBJECTIVES: We aimed to answer community-driven questions about the safety of UA and the consumption of urban-grown produce by measuring concentrations of nine metals in the soil, irrigation water, and urban-grown produce across urban farms and gardens in Baltimore, Maryland. METHODS: We measured concentrations of 6 nonessential [arsenic (As), barium (Ba), cadmium (Cd), chromium (Cr), lead (Pb), nickel (Ni)] and three essential [copper (Cu), manganese (Mn), zinc (Zn)] metals in soil, irrigation water, and 13 types of urban-grown produce collected from 104 UA sites. We compared measured concentrations to existing public health guidelines and analyzed relationships between urban soil and produce concentrations. In the absence of guidelines for metals in produce, we compared metals concentrations in urban-grown produce with those in produce purchased from farmers markets and grocery stores (both conventionally grown and U.S. Department of Agriculture–certified organic). RESULTS: Mean concentrations of all measured metals in irrigation water were below public health guidelines. Mean concentrations of nonessential metals in growing area soils were below public health guidelines for Ba, Cd, Pb, and Ni and at or below background for As and Cr. Though we observed a few statistically significant differences in concentrations between urban and nonurban produce items for some combinations, no consistent or discernable patterns emerged. DISCUSSION: Screening soils for heavy metals is a critical best practice for urban growers. Given limitations in existing public health guidelines for metals in soil, irrigation water, and produce, additional exposure assessment is necessary to quantify potential human health risks associated with exposure to nonessential metals when engaging in UA and consuming urban-grown produce. Conversely, the potential health benefits of consuming essential metals in urban-grown produce also merit further research. https://doi.org/10.1289/EHP9431

54 ENVIRONMENTAL SCIENCES↗

Working Safely at LANL during the COVID-19 Pandemic (Rev. 2)

The COVID-19 pandemic is an emerging, rapidly evolving public health emergency. The content of this course reflects the most up-to-date guidance and information from the Centers for Disease Control and Prevention (CDC), World Health Organization (WHO) and scientific literature available at the time the course was developed. Check the LANL COVID-19 Hub for the latest information and guidance. Updates to the course will be made as necessary to reflect evolving guidance form public health authorities and new data form the scientific literature.

60 APPLIED LIFE SCIENCES↗

Aerial Crosspolarized NQR-NMR: Buried Explosive Detection From a Safe Distance

Nuclear quadrupole resonance is a non-destructive detection and inspection technique with potential as a non-destructive test (NDT) tool. Establishment of the capability opens the door to its use in furthering the mission of the labs. There are many possible uses of the capability: explosive detection and stress/strain detection in epoxies are two of the more obvious and are the main results of this work. Enhancement of the signal-to-noise ratio (SNR) and improvements in the acquisition time of the experiment were key focuses of this work. These were achieved by combing special spin-lock pulse sequences with cross-polarization (CP) schemes to improve the signals with shorter acquisition times. A novel rotating magnetic field device was created to facilitate CP in the field. Implementation of these schemes provided a significant reduction in SNR/time.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Stabilization of Uranium Metal by Chloride Conversion-Economical, Safe, Scalable [Factsheet]

Researchers at Los Alamos National Laboratory have developed SUCCESS, a process to convert uranium metal to uranium tetrachloride enabling production of these valuable compounds for actinide science, molten salt nuclear reactors, and energy research. Conventional methods are problematic due to the oxide reduction processes use rare reagents and generate significant amounts of waste and hydride conversion process using chlorine at high temperature is hazardous. This new method using inexpensive reagents chemically transform uranium metal into uranium halide compounds under mild conditions. The facile conversion to stable uranium tetrachloride could reduce the need to mine uranium for uses other than nuclear, by recycling the uranium without oxidation. The Laboratory is interested in supporting further scale-up efforts using a Cooperative Research and Development Agreement (CRADA) or by granting a license to a qualified entity

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Science-integrated Artificial-intelligence for Flooding and precipitation Extremes (SAFE)

A grand challenge in hydrologic science is to understand why signals of climate change and variability, which are often visible in precipitation extremes at aggregate scales, are not consistently observed in the case of extreme flooding. However, a solution to this challenge may prove elusive unless the water cycle is viewed in an integrative manner. Thus, for riverine flooding, while Hortonian (infiltration excess) runoff may have stronger correlation with precipitation extremes and hence perhaps to warming trends or climate oscillators, Dunne (saturation excess) runoff may have a more complex relationships with time series of precipitation and with evaporation and transpiration, but rain-on-snow and snowmelt events may depend on land-surface and atmospheric temperatures. Atmospheric rivers and tropical cyclones lead to precipitation or flooding and are impacted by climate. Flooding assessments need to consider long-term baselines, evolving risk factors, coupled natural-human systems, and novel adaptation such as nature-inspired design.

54 ENVIRONMENTAL SCIENCES↗