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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Cassini Attitude Control Operations Flight Rules and How They are Enforced

The Cassini spacecraft was launched on October 15, 1997 and arrived at Saturn on June 30, 2004. It has performed detailed observations and remote sensing of Saturn, its rings, and its satellites since that time. Cassini deployed the European-built Huygens probe which descended through the Titan atmosphere and landed on its surface on January 14, 2005. Operating the Cassini spacecraft is a complex scientific, engineering, and management job. In order to safely operate the spacecraft, a large number of flight rules were developed. These flight rules must be enforced throughout the lifetime of the Cassini spacecraft. Flight rules are defined as any operational limitation imposed by the spacecraft system design, hardware, and software, violation of which would result in spacecraft damage, loss of consumables, loss of mission objectives, loss and/or degradation of science, and less than optimal performance. Flight rules require clear description and rationale. Detailed automated methods have been developed to insure the spacecraft is continuously operated within these flight rules. An overview of all the flight rules allocated to the Cassini Attitude Control and Articulation Subsystem and how they are enforced is presented in this paper.

Burk, Thomas↗
DOE OSTI2020

Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning

We assume that we are given a time series of data from a dynamical system and our task is to learn the flow map of the dynamical system. We present a collection of results on how to enforce constraints coming from the dynamical system in order to accelerate the training of deep neural networks to represent the flow map of the system as well as increase their predictive ability. In particular, we provide ways to enforce constraints during training for all three major modes of learning, namely supervised, unsupervised and reinforcement learning. In general, the dynamic constraints need to include terms which are analogous to memory terms in model reduction formalisms. Such memory terms act as a restoring force which corrects the errors committed by the learned flow map during prediction. For supervised learning, the constraints are added to the objective function. For the case of unsupervised learning, in particular generative adversarial networks, the constraints are introduced by augmenting the input of the discriminator. Finally, for the case of reinforcement learning and in particular actor-critic methods, the constraints are added to the reward function. In addition, for the reinforcement learning case, we present a novel approach based on homotopy of the action-value function in order to stabilize and accelerate training. We use numerical results for the Lorenz system to illustrate the various constructions.

Stinis, Panagiotis↗
DOE OSTI2012

ACE Learning Series - Enforcement Toolkit

The Building Energy Codes Program (BECP) developed this toolkit to help the enforcement community achieve higher levels of compliance with building energy codes. Although this toolkit is not intended for use by designers, developers, homeowners or renters, building owners, or building operators, it may provide those individuals some insight into the issues facing the enforcement community.

IECC, building information modeling, HVAC, new con↗
DOE OSTI2019

ESPC ESA Case Study: Energy Affordability at the Drug Enforcement Administration

The U.S. Drug Enforcement Administration (DEA) El Paso Intelligence Center (EPIC), located on Fort Bliss in El Paso, TX, installed 2.5 MW DC of photovoltaics (PV). This project was an energy sales agreement energy conservation measure (ESA ECM) using the U.S. Department of Energy (DOE) energy savings performance contract (ESPC) ENABLE contract vehicle. The project represents an economical clean-energy solution that provides excellent construction and other trades-related jobs, and provides information that will help future ESPC ESA projects provide cost savings to the government.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Where There’s a Way, There's a Will: The World Customs Organization's Capacity-Building in the Field of Strategic Trade Control Enforcement

The World Customs Organization’s (WCO) approach to capacity building in the domain of strategic trade control enforcement has been exceptionally effective. This article outlines what the WCO has done, documents some of the impacts, and examines factors contributing to its effectiveness. An important factor contributing to the WCO's success has been a focus on influencing senior policy makers at the national level in addition to upgrading working-level skills and abilities. This strategy in turn owes its success, at least in part, to the WCO’s legitimacy and norm-setting ability as a member-driven international organization, a customizable approach adaptive to various national circumstances, adherence to universal international mandates such as United Nations Security Council Regulation 1540, and the ability to couple training and operational activities.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

Efficient production of platelets from mouse embryonic stem cells by enforced expression of Gata2 in late hemogenic endothelial cells

Platelets are essential for blood circulation and coagulation. Previous study indicated that overexpression of Gata2 in differentiated mouse embryonic stem cells (ESCs) resulted in robust induction of megakaryocytes (Mks). To evaluate platelet production capacity of the Gata2-induced ESC-derived Mks, we generated iGata2-ESC line carrying the doxycycline-inducible Gata2 expression cassette. When doxycycline was added to day 5 hemogenic endothelial cells in the in vitro differentiation culture of iGata2-ESCs, c-Kit{sup −}Tie2{sup −}CD41{sup +} Mks were predominantly generated. These iGata2-ESC-derived Mks efficiently produced CD41{sup +}CD42b{sup +}CD61{sup +} platelets and adhered to fibrinogen-coated glass coverslips in response to thrombin stimulation. Transmission electron microscopy analysis demonstrated that the iGata2-ESC-derived platelets were discoid-shaped with α-granules and an open canalicular system, but were larger than peripheral blood platelets in size. These results demonstrated that an enforced expression of Gata2 in late HECs of differentiated ESCs efficiently promotes megakaryopoiesis followed by platelet production. This study provides valuable information for ex vivo platelet production from human pluripotent stem cells in future. -- Highlights: •Megakaryocytes are efficiently induced by Gata2 from ESC-derived day 5 HECs. •Gata2-induced ESC-derived megakaryocytes are c-Kit{sup −}Tie2{sup −}CD41{sup +}. •Gata2-induced ESC-derived megakaryocytes produce larger discoid-shaped platelets. •Gata2-induced ESC-derived platelets bind fibrinogen upon thrombin stimulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Exact enforcement of temporal continuity in sequential physics-informed neural networks

The use of deep learning methods in scientific computing represents a potential paradigm shift in engineering problem solving. One of the most prominent developments is Physics-Informed Neural Networks (PINNs), in which neural networks are trained to satisfy partial differential equations (PDEs). While this method shows promise, the standard version has been shown to struggle in accurately predicting the dynamic behavior of time-dependent problems. To address this challenge, methods have been proposed that decompose the time domain into multiple segments, employing a distinct neural network in each segment and directly incorporating continuity between them in the loss function of the minimization problem. In this work we introduce a method to exactly enforce continuity between successive time segments via a solution ansatz. This hard constrained sequential PINN (HCS-PINN) method is simple to implement and eliminates the need for any loss terms associated with temporal continuity. The method is tested for a number of benchmark problems involving both linear and non-linear PDEs. Examples include various first order time dependent problems in which traditional PINNs struggle, namely advection, Allen–Cahn, and Korteweg–de Vries equations. Furthermore, second and third order time-dependent problems are demonstrated via wave and Jerky dynamics examples, respectively. Notably, the Jerky dynamics problem is chaotic, making the problem especially sensitive to temporal accuracy. Finally, the numerical experiments conducted with the proposed method demonstrated superior convergence and accuracy over both traditional PINNs and the soft-constrained counterparts.

42 ENGINEERING↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Nuclear Forensics: Scientific Analysis Supporting Law Enforcement and Nuclear Security Investigations

In Nuclear Forensic Science, analytical chemists join forces with nuclear physicists, material scientists, radiochemists, and traditional forensic scientists, as well as experts in nuclear security, nuclear safeguards, law enforcement, and policy development, in an effort to deter nuclear smuggling. Nuclear forensic science, or “nuclear forensics,” aims to answer questions about nuclear material found outside of regulatory control, questions such as ‘where did this material come from?’ and ‘what is the intended use of the material?’ In this Feature, we provide a general overview of nuclear forensics, selecting examples of key “nuclear forensic signatures” which have allowed investigators to determine the identity of unknown nuclear material in real investigations.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Two-tiered enforcement of high-fidelity DNA ligation

DNA ligases catalyze the joining of DNA strands to complete DNA replication, recombination and repair transactions. To protect the integrity of the genome, DNA ligase 1 (LIG1) discriminates against DNA junctions harboring mutagenic 3'-DNA mismatches or oxidative DNA damage, but how such high-fidelity ligation is enforced is unknown. Here, X-ray structures and kinetic analyses of LIG1 complexes with undamaged and oxidatively damaged DNA unveil that LIG1 employs Mg 2+ -reinforced DNA binding to validate DNA base pairing during the adenylyl transfer and nick-sealing ligation reaction steps. Our results support a model whereby LIG1 fidelity is governed by a high-fidelity (HiFi) interface between LIG1, Mg 2+ , and the DNA substrate that tunes the enzyme to release pro-mutagenic DNA nicks. In a second tier of protection, LIG1 activity is surveilled by Aprataxin (APTX), which suppresses mutagenic and abortive ligation at sites of oxidative DNA damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Enforcing detailed balance in the Borgnakke–Larsen redistribution method with temperature dependent relaxation models

For decades, it has been observed that the commonly used Borgnakke–Larsen method for energy redistribution in Direct Simulation Monte Carlo codes fails to satisfy the principle of detailed balance when coupled to a wide variety of temperature dependent relaxation models, while seemingly satisfying detailed balance when coupled to others. Many attempts have been made to remedy the issue, yet much ambiguity remains, and no consensus appears in the literature regarding the root cause of the intermittent compatibility of the Borgnakke–Larsen method with temperature dependent relaxation models. This paper alleviates that ambiguity by presenting a rigorous theoretical derivation of the Borgnakke–Larsen method's requirement for satisfying detailed balance. Specifically, it is shown that the Borgnakke–Larsen method maintains detailed balance if and only if the probability of internal-energy exchange during a collision depends only on collision invariants (e.g., total energy). Here, the consequences of this result are explored in the context of several published definitions of relaxation temperature, including translational, total, and cell-averaged temperatures. Of particular note, it is shown that cell-averaged temperatures, which have been widely discussed in the literature as a way to ensure equilibrium is reached, also fail in a similar, although less dramatic, fashion when the aforementioned relationship is not enforced. The developed theory can be used when implementing existing or new relaxation models and will ensure that detailed balance is satisfied.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Constraining chaos: Enforcing dynamical invariants in the training of reservoir computers

Drawing on ergodic theory, we introduce a novel training method for machine learning based forecasting methods for chaotic dynamical systems. The training enforces dynamical invariants—such as the Lyapunov exponent spectrum and the fractal dimension—in the systems of interest, enabling longer and more stable forecasts when operating with limited data. The technique is demonstrated in detail using reservoir computing, a specific kind of recurrent neural network. Finally, results are given for the Lorenz 1996 chaotic dynamical system and a spectral quasi-geostrophic model of the atmosphere, both typical test cases for numerical weather prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

The reaction mechanism of methyl-coenzyme M reductase: How an enzyme enforces strict binding order

Methyl-coenzyme M reductase (MCR) is a nickel tetrahydrocorphinoid (coenzyme F430) containing enzyme involved in the biological synthesis and anaerobic oxidation of methane. MCR catalyzes the conversion of methyl-2-mercaptoethanesulfonate (methyl-SCoM) and N-7 -mercaptoheptanoylthreonine phosphate (CoB 7 SH) to CH 4 and the mixed disulfide CoBS-SCoM. In this study, the reaction of MCR from Methanothermobacter marburgensis , with its native substrates was investigated using static binding, chemical quench, and stopped-flow techniques. Rate constants were measured for each step in this strictly ordered ternary complex catalytic mechanism. Surprisingly, in the absence of the other substrate, MCR can bind either substrate; however, only one binary complex (MCR·methyl-SCoM) is productive whereas the other (MCR·CoB 7 SH) is inhibitory. Moreover, the kinetic data demonstrate that binding of methyl-SCoM to the inhibitory MCR·CoB 7 SH complex is highly disfavored ( K d = 56 mM). However, binding of CoB 7 SH to the productive MCR·methyl-SCoM complex to form the active ternary complex (CoB 7 SH·MCR(Ni I )·CH 3 SCoM) is highly favored ( K d = 79 μM). Only then can the chemical reaction occur ( k obs = 20 s -1 at 25 °C), leading to rapid formation and dissociation of CH 4 leaving the binary product complex (MCR(Ni II )·CoB 7 S - ·SCoM), which undergoes electron transfer to regenerate Ni(I) and the final product CoBS-SCoM. In conclusion, this first rapid kinetics study of MCR with its natural substrates describes how an enzyme can enforce a strictly ordered ternary complex mechanism and serves as a template for identification of the reaction intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Topological invariants of a filling-enforced quantum band insulator

Traditional ionic and covalent compound insulators arise from a commensuration between electron count and system volume. On the other hand, conventional topological insulators, outside of quantum Hall effect systems, do not typically display such a commensuration. Instead, they can undergo a phase transition to a trivial insulator that preserves the electron filling. Nevertheless, in some crystalline insulators, termed filling-enforced quantum band insulators (feQBIs), electron filling can dictate nontrivial topology in the insulating ground state. Currently, little is known about the relation between feQBIs and conventional topological invariants. In this work, we study such relations for a particularly interesting example of a half-filling feQBI that is realized in space group 106 with spinless electrons. In this work, we prove that any four-band feQBI in space group 106 with filling 2 must have a nontrivial topological invariant, namely, the $\mathbb{Z}$ 2 glide invariant, and thus must have a quantized magnetoelectric polarizability θ = π. We thus have found a three-dimensional example where electron filling and band topology are tied. Such a locking raises intriguing questions about the generality of the band-inversion paradigm in describing the transition between trivial and topological phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Enforcing End-to-end I/O Policies for Scientific Workflows using Software-Defined Storage Resource Enclaves

Data-intensive knowledge discovery requires scientific applications to run concurrently with analytics and visualization codes executing in situ for timely output inspection and knowledge extraction. Consequently, I/O pipelines of scientific workflows can be long and complex because they comprise many stages of analytics across different layers of the I/O stack of high-performance computing systems. Performance limitations at any I/O layer or stage can cause an I/O bottleneck resulting in greater than expected end-to-end I/O latency. In this paper, we present the design and implementation of a novel data management infrastructure called Software-Defined Storage Resource Enclaves (SIREN) at system level to enforce end-to-end policies that dictate an I/O pipeline's performance. SIREN provides an I/O performance interface for users to specify the desired storage resources in the context of in-situ analytics. If suboptimal performance of analytics is caused by an I/O bottleneck when data are transferred between simulations and analytics, schedulers in different layers of the I/O stack automatically provide the guaranteed lower bounds on I/O throughput. Lastly, our experimental results demonstrate that SIREN provides performance isolation among scientific workflows sharing multiple storage servers across two I/O layers (burst buffer and parallel file systems) while maintaining high system scalability and resource utilization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Filling-enforced quantum band insulators in spin-orbit coupled crystals

An early triumph of quantum mechanics was the explanation of metallic and insulating behavior based on the filling of electronic bands. A complementary, classical picture of insulators depicts electrons as occupying localized and symmetric Wannier orbitals that resemble atomic orbitals. We report the theoretical discovery of band insulators for which electron filling forbids such an atomic description. We refer to them as filling-enforced quantum band insulators (feQBIs) because their wave functions are associated with an essential degree of quantum entanglement. Like topological insulators, which also do not admit an atomic description, feQBIs need spin-orbit coupling for their realization. However, they do not necessarily support gapless surface states. Instead, the band topology is reflected in the insulating behavior at an unconventional filling. We present tight binding models of feQBIs and show that they only occur in certain nonsymmorphic, body-centered cubic crystals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

$\mathscr{PT}$ symmetry enforced twin exchange as the origin of chirality-induced spin selectivity

Chiral molecules, ubiquitous in chemistry and biology, can differentiate electrons by their spin, a phenomenon known as chirality-induced spin selectivity (CISS). Despite its robustness and technological relevance, CISS has resisted conventional explanation: Spin-orbit coupling (SOC) models cannot fully account for the observed magnitude, room-temperature persistence, or equilibrium signatures. Here, we argue that structural chirality enforces a twin-pair exchange mechanism via the indistinguishability principle, which intrinsically couples spin and spatial degrees of freedom such that wave functions cannot be factorized into spin and spatial components. We derive an effective Hamiltonian that describes both transport and equilibrium CISS phenomena and is non-Hermitian. However, the inherent pseudo-Hermiticity, with $\mathscr{PT}$ symmetry as a special case, ensures real eigenvalues and thermodynamic consistency. We demonstrate that our framework is a step toward resolving long-standing anomalies of CISS. It situates CISS alongside equilibrium symmetry-breaking phenomena such as ferromagnetism and superconductivity, with implications for spintronics, catalysis, and the origins of biological homochirality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗