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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

A Scalable and Robust Multi-Agent Approach to Distributed Optimization

Modularizing a large optimization problem so that the solutions to the subproblems provide a good overall solution is a challenging problem. In this paper we present a multi-agent approach to this problem based on aligning the agent objectives with the system objectives, obviating the need to impose external mechanisms to achieve collaboration among the agents. This approach naturally addresses scaling and robustness issues by ensuring that the agents do not rely on the reliable operation of other agents We test this approach in the difficult distributed optimization problem of imperfect device subset selection [Challet and Johnson, 2002]. In this problem, there are n devices, each of which has a "distortion", and the task is to find the subset of those n devices that minimizes the average distortion. Our results show that in large systems (1000 agents) the proposed approach provides improvements of over an order of magnitude over both traditional optimization methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents fail midway through the simulation) the system remains coordinated and still outperforms a failure-free and centralized optimization algorithm.

Tumer, Kagan↗
DOE OSTI2023

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Integrated GW Farm ABM

This Data Repository includes data used for the integrated groundwater- farm ABM model, raw model output from scenario ensemble, and processed outputs that isolate the groundwater storage depletion outcomes for the 35,000 farm cells. Model Inputs: Farm ABM Inputs: This folder contains the input data used by the integrated groundwater - farm ABM modelling script (Python file) used for the high performance computing (HPC) experiments. The sub-folder "data inputs" contains all of the farm attribute data, while the three files in the folder have the hydrogeological data lookup table (NLDAS Cost Curve Attributes.csv), a lookup table (Theis well function table.csv) for the groundwater cost curve function, and the farm indexes and corresponding NLDAS ids for all of the cells run in this experiment (nldas farms subset final.csv). NLDAS Cost curve hydrogeological data: Hydrogeological data aggregated to 1/8 degree resolution and aligned with the NLDAS grid. Parameters include: water depth below ground surface [meters], subsurface porosity [unitless], aquifer depth from ground surface to aquifer bottom [meters], annual average recharge (USGS: mm, Doll: meters), and three different hydraulic conductivity (K) values (meters/day). The three K values represent the mean value from Gleeson et al. (2018), one standard deviation above the mean from Gleeson et al. (2018), and the de Graaf et al. 2020 modifications to certain lithologies. Additional information about these datasets and their processing are documented in the supplement to Yoon et al. 2025 (in review). Output: Raw outputs: This folder contains a .zip file that has model outputs for the entire scenario ensemble. There is one csv for each farm id, using the format "farm farmid cases.csv". The relationship between the farm id and NLDAS id is defined by the "nldas farms subset final.csv" located in the Farm ABM Inputs folder. Each csv has 625 rows, corresponding to 625 combinations of different scenario parameter values. Each row (scenario) represents the outcome of a 100 year simulation. Columns define scenario settings and summary statistics for each scenario. The first four columns define the scenario settings: "hydro ratio," "econ ratio," "K scenario," and "gamma scenario." The hydro and econ ratios are values passed to the modeling script that influence multipliers for other model parameters, as documented in the supplement to Yoon et al. 2025 (in review). The gamma multiplier is a coefficient multiplier applied to the baseline gamma values (values below 1 represent lower unobserved costs compared to baseline, values above 1 represent higher costs). The K scenario names represent K values of: "low": 0.5 m/d, "int 1": 2.5 m/d, "int 2": 10 m/d, "high": 50 m/d, and "gleeson": mean Gleeson K value. "Perc vol depleted" is the fraction of groundwater depleted at the end of the 100 simulation. Processed Output: Derived depletion outcomes from raw outputs: All of the individual csv files from the Raw outputs were aggregated into a single file that has the scenario settings and fraction depletion "Perc vol depleted" for every farm cell, for every scenario. The other two files define relationships between the farm id, NLDAS id, and local and major aquifer units, used for aquifer-level depletion analysis.

Agent based modeling↗
DOE OSTI2022

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Forced Patterns of Sea Level Rise in the Community Earth System Model Large Ensemble From 1920 to 2100

To provide context for observed sea level rise, the forced response (FR) in dynamic sea level (DSL) during the 20th and 21st centuries is examined in the Community Earth System Model Large Ensemble (LE). After accounting for simulation drift, which in the LE is sizable, the DSL FR is found to be complex, both in space and time. Its evolving character is suggested to arise from both the diversity and transient evolution of climate forcing agents and the slow adjustment timescales of the intermediate and deep oceans. Nonetheless, various intervals of spatially coherent change simulated for the recent past and near future are identified, and their characteristics and associated driving mechanisms are identified and discussed. The mid- to late-20th century DSL FR is characterized by an hemispherically asymmetric pattern of change, with depressed rates of rise in the northern oceans. There is also a dipole of change in the Southern Ocean caused by changes in near-surface zonal winds. Through the late 20th and early 21st centuries, a different pattern of rise emerges with elevated rates in the tropics and depressed rates at high latitudes. Zonal and interbasin variations characterize both intervals and involve the pattern and depth of anomalous ocean heat content storage and spatial contrasts in the expansion coefficient tied mainly to base state temperature, with greater rates of rise in warm regions per unit warming. Finally, the relative roles of surface flux and ocean convergence anomalies are examined.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Combined light- and heat-induced shape memory behavior of anthracene-based epoxy elastomers

Abstract The development of multi-stimuli-responsive shape memory polymers has received increasing attention because of its scientific and technological significance. In this work, epoxy elastomers with reversible crosslinks are synthesized by polymerizing an anthracene-functionalized epoxy monomer, a diepoxy comonomer, and a dicarboxylic acid curing agent. The synthesized elastomers exhibit active responses to both light and heat enabled by the incorporated anthracene groups. When exposed to 365 nm UV light, additional crosslinking points are created by the photo-induced dimerization of pendant anthracene groups. The formation of the crosslinking points increases modulus and glass transition temperature of the elastomers, allowing for the fixation of a temporary shape at room temperature. The temporary shape remains stable until an external heat stimulus is applied to trigger the scission of the dimerized anthracene, which reduces the modulus and glass transition temperature and allows the elastomers to recover their original shapes. The effects of external stimuli on the thermal and dynamic mechanical properties of the elastomers are investigated experimentally and are correlated with molecular dynamics simulations that reveal the changes of structure and dynamics of the anthracene molecules and flexible chains.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings

As wind energy plays a growing role in the energy sector, new methods for controlling wind turbines and wind farms to maximize performance are garnering industry interest. A developing body of research treats the entire wind farm as a control system, with individual turbines acting as agents in a network, allowing farm-level objectives to be considered. Two promising developments in this research are wake steering control, which seeks to increase the power generated at a wind farm by directing the wakes of upstream turbines away from downstream ones, and communication-based spatial filtering, which seeks to improve the quality of information used by turbine- and farm-level controllers by combining measurements of the wind field collected at the individual turbines. The latter method has been shown to improve the estimates of wind direction at the turbines; however, the resulting potential for increased power capture warrants further investigation. With this paper, we begin to address this gap by combining wake steering with wind direction spatial filtering. To do so, we present a preliminary method for assessing the power capture of dynamic controllers using wind farm codes designed for time-averaged simulation. This allows us to generate results much more rapidly than would be possible using high-fidelity wind farm simulators and may be useful in many wind farm control design applications.

17 WIND ENERGY↗
NASA NTRS1992

Development of microcomputer-based mental acuity tests

Recent disasters have focused attention on performance problems due to the use of alcohol and controlled substances in the workplace. Environmental stressors such as thermal extremes, mixed gases, noise, motion, and vibration also have adverse effects on human performance and operator efficiency. However, the lack of a standardized, sensitive, human performance assessment battery has probably delayed the systematic study of the deleterious effects of various toxic chemicals and drugs at home and in the workplace. The collective goal of the research reported here is the development of a menu of tests embedded in a coherent package of hardware and software that may be useful in repeated-measures studies of a broad range of agents that can degrade human performance. A menu of 40 tests from the Automated Performance Test System (APTS) is described, and the series of interlocking studies supporting its development is reviewed. The APTS tests, which run on several versions of laptop portables and desktop personal computers, have been shown to be stable, reliable, and factorially rich, and to have predictive validities with holistic measures of intelligence and simulator performances. In addition, sensitivity studies have been conducted in which performance changes due to stressors, agents, and treatments were demonstrated. We believe that tests like those described here have prospective use as an adjunct to urine testing for the screening for performance loss of individuals who are granted access to workplaces and stations that impact public safety.

Non-NASA Center↗
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2006

Adjustably Autonomous Multi-agent Plan Execution with an Internal Spacecraft Free-Flying Robot Prototype

We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.

Dorais, Gregory A.↗
NASA NTRS2012

Laboratory Shock Experiments on Basalt - Iron Sulfate Mixes at Approximately 40-50 GPa and Their Relevance to the Martian Regolith Component Present in Shergottites

Basaltic shergottites such as Shergotty, Zagami and EET79001 contain impact melt glass pockets that are rich in Martian atmospheric gases [1] and are known as gas-rich impact-melt (GRIM) glasses. These glasses show evidence for the presence of a Martian regolith component based on Sm and Kr isotopic studies [2]. The GRIM glasses are sometimes embedded with clusters of innumerable micron-sized iron-sulfide blebs associated with minor amounts of iron sulfate particles [3, 4]. These sulfide blebs are secondary in origin and are not related to the primary igneous sulfides occurring in Martian meteorites. The material comprising these glasses arises from the highly oxidizing Martian surface and sulfur is unlikely to occur as sulfide in the Martian regoilith. Instead, sulfur is shown to occur as sulfate based on APXS and Mossbauer results obtained by the Opportunity and Spirit rovers at Meridiani and Gusev [5]. We have earlier suggested that the micron-sized iron sulfide globules in GRIM glasses were likely produced by shock-reduction of iron sulfate occurring in the regolith at the time when the GRIM glasses were produced by the meteoroid impact that launched the Martian meteorites into space [6]. As a result of high energy deposition by shock (approx. 40-60 GPa), the iron sulfate bearing phases are likely to melt along with other regolith components and will get reduced to immiscible sulfide fluid under reducing conditions. On quenching, this generates a dispersion of micron-scale sulfide blebs. The reducing agents in our case are likely to be H2 and CO which were shock-implanted from the Martian atmosphere into these glasses along with the noble gases. We conducted lab simulation experiments in the Lindhurst Laboratory of Experimental Geophysics at Caltech and the Experimental Impact Laboratory at JSC to test whether iron sulfide globules can be produced by impact-driven reduction of iron sulfate by subjecting Columbia River Basalt (CRB) and ferric sulfate mixtures to shock pressures between 40 and 50 GPa under reducing conditions. The experimental products from the recovered samples were analyzed by SEM and microprobe techniques at JSC.

Rao, M. N.↗
DOE OSTI2020

Agent-Based Coordination Scheme for PV Integration (ABC4PV)

Renewables and especially photovoltaics (PV) have benefitted significantly from a host of incentives and policies targeted toward enhanced integration and adoption of specific energy technologies. However, with the push to move forward into a subsidy-free market framework, behind-the-meter residential PV applications have generally struggled to retain their value (unlike utility scale and commercial projects) [1]. This project focused on developing control-theoretic solutions aimed at improving the integration and interaction of behind-the-meter residential PV with other distribution system assets (controllable and non-controllable) to enhance the integrated value of residential PV. To this end, a suite of decentralized control methodologies have been developed to enable effective coordination and control of behind-the-meter residential load customers’ PV, battery storage systems (BSS), controllable loads and other similar assets within a distribution feeder. This interaction aims at procuring energy savings and, thus, energy bill savings. The main source of savings is drawn from reducing the effect of demand charge pricing and is realized at the feeder level, assuming community level interaction and management among the aforementioned assets. Optimal control of the assets is implemented with a distributed optimization methodology, leveraging consensus-based algorithms. The results gathered from the optimal control simulations demonstrates that the savings can be duly achieved and the algorithm decision times (to dynamically control asset set points, for example) are fast. As for the overall efficiency of PV+BSS systems, to procure energy savings from curtailment of the demand charge pricing effects, the optimal control is set up so as to minimize the variance of the load for all customers, throughout a feeder and throughout time in a rolling horizon scheduling with model predictive control. The control takes into account inter-temporal electrochemical storage (battery) degradation costs: specifically, we have developed a long-term lifetime model for the BSS that weighs in the effect of the degradation factor in the dispatch formulations, thus, a considerable operating cost that affects energy decision making. The levelized cost of energy (LCOE – redefined for the purpose of quantifying asset integration effectiveness through the customers’ energy cost) is shown to be below the threshold set for the combined PV+BSS topology of $ 0.14/kWh for multiple cases of PV penetration all the way up to 50%, provided that a policy of shared ownership of and savings is in place. Further, the LCOE calculated for the case before the deployment PV+BSS systems is also achievable, i.e. the deployment of PV+BSS, if planned and scheduled optimally. will have no effect on customers’ energy costs. From the control methodology viewpoint, the developed consensus-based algorithms are shown to converge for a wide range of problem cases (spanning normal operating scenarios and contingencies), guaranteeing dispatch solutions under forecasting errors, communication break-downs and cyber-security attacks. The proposed control solutions are scalable and real-time implementable, with dispatch computations and device set-point updates converging in less than 2s in most practical instances of the above events.

14 SOLAR ENERGY↗
DOE OSTI2023

Purification of Lithium-Ion Battery Black Mass through Tailored Alkaline Corrosion

Obtaining high-purity material outputs is crucial to the viability of novel process aimed at direct recycling of lithium-ion batteries. Metallic impurities in recycled cathodes have been shown to inhibit performance, thereby threatening mainstream acceptance of recycled battery products. Thus, shredded black mass (BM) must be purified to remove metallic contaminants, and specifically Al and Cu originating from the electrode current collectors. We herein explore a process to ionize solid copper and aluminum to ionic form based on tailored alkaline chemistry, without incurring damage to the target cathode material (Li(NixMnyCo1-x-y)O2; NMC). Al and Cu corrosion may be enhanced through the addition of chloride salt, elevated temperatures, and the use of ultrasonication - all of which disrupt the formation of passivating films on the metallic surface, and thereby increase corrosion rate. We demonstrate optimized parameters for Al and Cu corrosion both from a kinetic and overall process cost perspective. Further, we analyze the impact of these conditions on the structural (XRD, SEM), chemical (EDS, ICP), and electrochemical (impedance, cycling, dQ/dV) properties of NMC, and suggest that the present purification method does not significantly disrupt NMC performance. Finally, we present preliminary results from a promising bench-scale demonstration of this purification process applied to a simulated black mass.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
DOE OSTI2022

Structural and dynamic effects of paraoxon binding to human acetylcholinesterase by X-ray crystallography and inelastic neutron scattering

Organophosphorus (OP) compounds, including nerve agents and some pesticides, covalently bind to the catalytic serine of human acetylcholinesterase (hAChE), thereby inhibiting acetylcholine hydrolysis necessary for efficient neurotransmission. Oxime antidotes can reactivate the OP-conjugated hAChE, but reactivation efficiency can be low for pesticides, such as paraoxon (POX). Understanding structural and dynamic determinants of OP inhibition and reactivation can provide insights to design improved reactivators. Here, in this study, X-ray structures of hAChE with unaged POX, with POX and oximes MMB4 and RS170B, and with MMB4 are reported. A significant conformational distortion of the acyl loop was observed upon POX binding, being partially restored to the native conformation by oximes. Neutron vibrational spectroscopy combined with molecular dynamics simulations showed that picosecond vibrational dynamics of the acyl loop soften in the ~20–50 cm –1 frequency range. The acyl loop structural perturbations may be correlated with its picosecond vibrational dynamics to yield more comprehensive template for structure-based reactivator design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator

Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.

Ham, Sang woo↗
DOE OSTI2023

Gating interactions steer loop conformational changes in the active site of the L1 metallo-β-lactamase

β-Lactam antibiotics are the most important and widely used antibacterial agents across the world. However, the widespread dissemination of β-lactamases among pathogenic bacteria limits the efficacy of β-lactam antibiotics. This has created a major public health crisis. The use of β-lactamase inhibitors has proven useful in restoring the activity of β-lactam antibiotics, yet, effective clinically approved inhibitors against class B metallo-β-lactamases are not available. L1, a class B3 enzyme expressed by Stenotrophomonas maltophilia , is a significant contributor to the β-lactam resistance displayed by this opportunistic pathogen. Structurally, L1 is a tetramer with two elongated loops, α3-β7 and β12-α5, present around the active site of each monomer. Residues in these two loops influence substrate/inhibitor binding. To study how the conformational changes of the elongated loops affect the active site in each monomer, enhanced sampling molecular dynamics simulations were performed, Markov State Models were built, and convolutional variational autoencoder-based deep learning was applied. The key identified residues (D150a, H151, P225, Y227, and R236) were mutated and the activity of the generated L1 variants was evaluated in cell-based experiments. The results demonstrate that there are extremely significant gating interactions between α3-β7 and β12-α5 loops. Taken together, the gating interactions with the conformational changes of the key residues play an important role in the structural remodeling of the active site. These observations offer insights into the potential for novel drug development exploiting these gating interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

Source record↗
DOE OSTI2023

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗