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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 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS1994

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Hein, C.↗

NASA NTRS1991

Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

Gabrielian, Armen↗

NASA NTRS2021

Context and future directions for integrating forest carbon into sub-national climate mitigation planning in the RGGI region of the U.S.

International frameworks for climate mitigation that build from national actions have been developed under the United National Framework Convention on Climate Change and advanced most recently through the Paris Climate Agreement. In parallel, sub-national actors have set greenhouse gas (GHG) reduction goals and developed corresponding climate mitigation plans. Within the U.S., multi-state coalitions have formed to facilitate coordination of related science and policy. Here, utilizing the forum of the NASA Carbon Monitoring System’s Multi-State Working Group, we collected and reviewed climate mitigation plans for 11 states in the Regional Greenhouse Gas Initiative region of the Eastern U.S. For each state we reviewed the (a) policy framework for climate mitigation, (b) GHG reduction goals, (c) inclusion of forest activities in the state’s climate action plan, (d) existing science used to quantify forest carbon estimates, and (e) stated needs for forest carbon monitoring science. Across the region, we found important differences across all categories. While all states have GHG reduction goals and framework documents, nearly three-quarters of all states do not account for forest carbon when planning GHG reductions; those that do account for forest carbon use a variety of scientific methods with various levels of planning detail and guidance. We suggest that a common, efficient, standardized forest carbon monitoring system would provide important benefits to states and the geographic region as a whole. In addition, such a system would allow for more effective transparency and progress tracking to support state, national, and international efforts to increase ambition and implementation of climate goals.

Rachel L Lamb↗

DOE OSTI2022

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗

DOE OSTI2024

Superconducting microwave cavities and qubits for quantum information systems

Superconducting microwave cavities featuring ultrahigh Q-factors, which measure the efficiency of energy storage in relation to energy loss in a system, are revolutionizing quantum computing by providing long coherence times exceeding 1 ms, crucial for the development of scalable multi-qubit quantum systems with low error rates. Here, in this work, we provide an in-depth analysis of recent advances in ultrahigh Q-factor cavities, integration of Josephson junction-based qubits, and bosonic-encoded qubits in 3D cavities. We examine the sources of quantum state dephasing caused by damping and noise mechanisms in cavities and qubits, highlighting the critical challenges that need to be addressed to achieve even higher coherence times. We critically survey the latest progress made in implementing single 3D qubits using superconducting materials, normal metals, and multi-qubit and multi-state quantum systems. Our work sheds light on the promising future of this research area, including novel materials for cavities and qubits, modes with nontrivial topological properties, error correction techniques for bosonic qubits, and new light–matter interaction effects.

3D printing↗

NASA NTRS1974

CARETS: An experimental regional information system using ERTS data

The U. S. Geological Survey CARETS (Central Atlantic Regional Ecological Test Site)/ERTS investigation is testing the applicability of ERTS data as input to an environmental information system for a multi-state mid-Atlantic region surrounding the Chesapeake and Delaware Bays. The information system framework encompasses a flow of information through several stages from sensor to user, and involving evaluation and feedback from several potential users. Basic assumptions of the CARETS project model are that there is a measurable environmental impact associated with land use and land use change as determined with remote sensor data, and that the ERTS derived land use data sets, when properly calibrated, may thus provide regional planners and administrators with a shortcut to an understanding of the environmental changes that are going on in their regions.

Alexander, R. H.↗

DOE OSTI2024

Developing a Robust Market for CHP: A Plan for Fostering Economic Development, Business Competitiveness and Resiliency in the Mid-Atlantic Region

The Department of Energy’s Mid Atlantic Combined Heat and Power Technical Assistance Partnership (MA CHP TAP) was established to develop public-private partnerships to advance the technology, policies, and programmatic support for combined heat and power (CHP), including its application in microgrids, heat to power and district energy. The MA CHP TAP’s work includes education and outreach as well as technical assistance to a variety of stakeholders including end-users (commercial, industrial, institutional and more), state decision makers, electric and gas utilities, trade associations and non-profit organizations. This assistance includes evaluating the economic, energy, reliability and environmental value of proposed systems. The MA CHP TAP represents the multi-state Mid- Atlantic region and is the CHP expert in the region who provides fact-based, un-biased information on CHP, including technologies, project development, project financing, local electric and natural gas utility interfaces, and related state best practice policies.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Enabling Sustainable Landscape Design for Continual Improvement of Operating Bioenergy Supply Systems

This unique and highly effective project catalyzed collaboration among government, university, and private sector partners through a multi-state research and technology transfer project designed to support continuous improvement of bioenergy feedstock supply systems. Conceived and built upon the foundation created by prior DOE investments in the Billion Ton Study, Sun Grant Regional Project, and many other feedstock production, harvest, storage and transportation studies, this project addressed seven tasks with more than 29 subtasks. All goals were met with key accomplishments being: (1) on-farm establishment of potential perennial plant mixtures that could not only become sustainable feedstock sources but also enhance soil health, (2) a reduction in potential wind and water erosion by improving corn stover harvest techniques and incorporating cover crops into current row-crop production systems, (3) reduced potential for surface and groundwater contamination while also increasing potential biodiversity and sustainability of Midwestern USA landscapes, and (4) development of site-specific land management, data visualization, and sustainability assessment tools. Twenty-two Case Studies highlighting accomplishments and lessons learned through this public-private partnership investment are incorporated into this final report. On-farm and replicated field plot studies were used to provide the real-world data needed to verify baseline assumptions for extensive feedstock logistic modeling and greenhouse gas (GHG) assessments needed to develop sustainable bioenergy and bio-product industries at national and international scales.

09 BIOMASS FUELS↗

NASA NTRS2013

The Evolution of Software and Its Impact on Complex System Design in Robotic Spacecraft Embedded Systems

The growth in computer hardware performance, coupled with reduced energy requirements, has led to a rapid expansion of the resources available to software systems, driving them towards greater logical abstraction, flexibility, and complexity. This shift in focus from compacting functionality into a limited field towards developing layered, multi-state architectures in a grand field has both driven and been driven by the history of embedded processor design in the robotic spacecraft industry.The combinatorial growth of interprocess conditions is accompanied by benefits (concurrent development, situational autonomy, and evolution of goals) and drawbacks (late integration, non-deterministic interactions, and multifaceted anomalies) in achieving mission success, as illustrated by the case of the Mars Reconnaissance Orbiter. Approaches to optimizing the benefits while mitigating the drawbacks have taken the form of the formalization of requirements, modular design practices, extensive system simulation, and spacecraft data trend analysis. The growth of hardware capability and software complexity can be expected to continue, with future directions including stackable commodity subsystems, computer-generated algorithms, runtime reconfigurable processors, and greater autonomy.

software↗

NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

DOE OSTI2025

Forecasting EV Charging Demand on the Distribution System

The U.S. transportation and electricity sectors have historically operated independently, but the growth of electric vehicles (EVs) is driving their convergence. After decades of stagnant demand, utilities must prepare for rising load growth, driven in part by transportation electrification. Utilities must anticipate when and where these new loads will materialize to effectively manage EV growth and maintain grid reliability. This presentation outlines NREL's approach to developing high-resolution EV load datasets for distribution planning, with insights from the Multi-State Transportation Electrification Impact Study on EV and load forecasting, infrastructure requirements, and managed charging strategies.

25 ENERGY STORAGE↗

DOE OSTI2021

High-fidelity first principles nonadiabaticity: diabatization, analytic representation of global diabatic potential energy matrices, and quantum dynamics

We report nonadiabatic dynamics, which goes beyond the Born–Oppenheimer approximation, has increasingly been shown to play an important role in chemical processes, particularly those involving electronically excited states. Understanding multistate dynamics requires rigorous quantum characterization of both electronic and nuclear motion. However, such first principles treatments of multi-dimensional systems have so far been rather limited due to the lack of accurate coupled potential energy surfaces and difficulties associated with quantum dynamics. In this Perspective, we review recent advances in developing high-fidelity analytical diabatic potential energy matrices for quantum dynamical investigations of polyatomic uni- and bi-molecular nonadiabatic processes, by machine learning of high-level ab initio data. Special attention is paid to methods of diabatization, high fidelity construction of multi-state coupled potential energy surfaces and property surfaces, as well as quantum mechanical characterization of nonadiabatic nuclear dynamics. To illustrate the tremendous progress made by these new developments, several examples are discussed, in which direct comparison with quantum state resolved measurements led to either confirmation of the observation or sometimes reinterpretation of the experimental data. The insights gained in these prototypical systems greatly advance our understanding of nonadiabatic dynamics in chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Multi-State Transportation Electrification Impact Study: Preparing the Grid for Light-, Medium-, and Heavy-Duty Electric Vehicles

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Transportation Electrification Impact Study (TEIS)

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

NASA NTRS2008

Ground-Based Lidar Measurements During the CALIPSO and Twilight Zone (CATZ) Campaign

The CALIPSO and Twilight Zone (CATZ) field campaign was carried out between June 26th and August 29th of 2007 in the multi-state Maryland-Virginia-Pennsylvania region of the U.S. to study aerosol properties and cloud-aerosol interactions during overpasses of the CALIPSO satellite. Field work was conducted on selected days when CALIPSO ground tracks occurred in the region. Ground-based measurements included data from multiple Cimel sunphotometers that were placed at intervals along a segment of the CALIPSO ground-track. These measurements provided sky radiance and AOD measurements to enable joints inversions and comparisons with CALIPSO retrievals. As part of this activity, four ground-based lidars provided backscatter measurements (at 523 nm) in the region. Lidars at University of Maryland Baltimore County (Catonsville, MD) and Goddard Space Flight Center (Greenbelt, MD) provided continuous data during the campaign, while two micro-pulse lidar (MPL) systems were temporarily stationed at various field locations directly on CALIPSO ground-tracks. As a result, thirteen on-track ground-based lidar observations were obtained from eight different locations in the region. In some cases, nighttime CALIPSO coincident measurements were also obtained. In most studies reported to date, ground-based lidar validation efforts for CALIPSO rely on systems that are at fixed locations some distance away from the satellite ground-track. The CATZ ground-based lidar data provide an opportunity to examine vertical structure properties of aerosols and clouds both on and off-track simultaneously during a CALIPSO overpass. A table of available ground-based lidar measurements during this campaign will be presented, along with example backscatter imagery for a number of coincident cases with CALIPSO. Results indicate that even for a ground-based measurements directly on-track, comparisons can still pose a challenge due to the differing spatio-temporal properties of the ground and satellite observations. The multiple-lidar data during the CATZ campaign is expected to provide additional information on regional aerosol and cloud dynamics for give overpass, and enable a more realistic assessment of ground-to-satellite correlations. Future work is anticipated to finalize calibrated lidar backscatter profiles and utilization of wind trajectory information to further enable comparisons to CALIPS data.

Berkoff, Timothy↗

DOE OSTI2023

Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)

For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

PotLib 2023: New version of a potential energy surface library for chemical systems

POTLIB is a library of global and semiglobal potential energy surface subprograms. The library currently features 410 entries, including both single-state entries and multi-state entries. When one calls the routine of a single-state entry, it returns the ground-electronic-state adiabatic potential energy surface at the input geometry. In addition, some entries also return the gradient of the surface. Further, when one calls a multi-state entry, it returns a diabatic potential energy matrix (DPEM). If the entry also has the gradient of the DPEM, one can compute adiabatic surfaces, their gradients, and the nonadiabatic coupling vectors (NACs) from the DPEM and its gradient by diagonalization. Some but not all the routines conform to one of a set of standard interfaces. The goal is to facilitate chemical dynamics research by collecting and disseminating a comprehensive collection of state-of-the-art potential energy routines (developed by a wide, international group of researchers) with systematic and well-defined interfaces for use with chemical dynamics programs. Systems in the library include CHArO 2 , CHN 2 O + , CH 2 O, CH 2 O 2 , CH 3 N 2 , CH 3 O, CH 4 , CH 4 Br, CH 4 Cl, CH 4 F, CH 4 O, CH 4 OCl, CH 4 OF, CH 4 OH, CH 5 , CH$^{+}_{5}$, CH 5 N, CH 5 O 2 , CH 8 O 2 , C 2 H 2 N 2 O, C 2 H 2 O, C 2 H 4 N, C 2 H 4 O 4 , C 2 H 6 Cl, C 2 H 6 F, C 2 H 6 H, C 2 H 6 O, C 2 H 6 OH, C 2 H 7 , C 2 O 2 , C 3 H 4 O 2 , C 3 H 7 NO, C 6 H 6 O, C 6 H 6 S, C 7 H8S, HBrCl, HCl 2 , HF 2 , HI 2 , HLiF, HNaF, HO 2 , HO 3 , HOBr, HSiO, H 2 Br, H 2 ClO, H 2 F, H 2 F 2 , H 2 FO, H 2 Na, H 2 O, H 2 O 2 , H 2 OBr, H 3 , H 3 Cl, H 3 ClN, H 3 ClO, H 3 N, H 3 O, H 3 O 2 , H$^{+}_{3}$, H 3 S, H 4 ClSi, H 4 N, H 4 NO, H 4 O 2 , H 5 GeO, H 5 Si, H$^{+}_{7}$, Al m H n , Al n , Ar N O, K 2 Rb 2 , NO 2 , N 2 O, N 2 O 2 , N 3 , N 4 , O 3 , and O 4 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Excited state electronic structure of dimethyl disulfide involved in photodissociation at ∼200 nm

Dimethyl disulfide (DMDS), one of the smallest organic molecules with an S–S bond, serves as a model system for understanding photofragmentation in polypeptides and proteins. Prior studies of DMDS photodissociation excited at ∼266 nm and ∼248 nm have elucidated the mechanisms of S–S and C–S bond cleavage, which involve the lowest excited electronic states S 1 and S 2 . Far less is known about the dissociation mechanisms and electronic structure of relevant excited states of DMDS excited at ∼200 nm. Herein we present calculations of the electronic structure and properties of electronic states S 1 –S 6 accessed when DMDS is excited at ∼200 nm. Our analysis includes a comparison of theoretical and experimental UV spectra, as well as theoretically predicted one-dimensional cuts through the singlet and triplet potential energy surfaces along the S–S and C–S bond dissociation coordinates. Finally, we present calculations of spin–orbit coupling constants at the Franck–Condon geometry to assess the likelihood of ultrafast intersystem crossing. We show that choosing an accurate yet computationally efficient electronic structure method for calculating the S 0 –S 6 potential energy surfaces along relevant dissociation coordinates is challenging due to excited states with doubly excited character and/or mixed Rydberg-valence character. Our findings demonstrate that the extended multi-state complete active space second-order perturbation theory (XMS-CASPT2) balances this computational efficiency and accuracy, as it captures both the Rydberg character of states in the Franck–Condon region and multiconfigurational character toward the bond-dissociation limits. In conclusion, we compare the performance of XMS-CASPT2 to a new variant of equation of motion coupled cluster theory with single, double, and perturbative triple corrections, EOM-CCSD(T)(a)*, finding that EOM-CCSD(T)(a)* significantly improves the treatment of doubly excited states compared to EOM-CCSD, but struggles to quantitatively capture asymptotic energies along bond dissociation coordinates for these states.

Rishi, Varun↗