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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Organizing bacterial vortex lattices by periodic obstacle arrays

Recent experiments have shown that the complex spatio-temporal vortex structures emerging in active fluids are susceptible to weak geometrical constraints. This observation poses the fundamental question of how boundary effects stabilize a highly ordered pattern from seemingly turbulent motion. Here we show, by a combination of continuum theory and experiments on a bacterial suspension, how artificial obstacles guide the flow profile and reorganize topological defects, which enables the design of bacterial vortex lattices with tunable properties. To this end, the continuum model is extended by appropriate boundary conditions. Beyond the stabilization of square and hexagonal lattices, we also provide a striking example of a chiral, antiferromagnetic lattice exhibiting a net rotational flow, which is induced by arranging the obstacles in a Kagome-like array. Recent experiments showed that weak geometrical constraints can organize topological defects in turbulent bacterial suspensions. Here, the authors use a continuum model to study the connection between symmetry and stability of emergent vortex patterns and the geometry of constraining pillar arrays.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Experimental Realization of Discrete Time Quasicrystals

Floquet (periodically driven) systems can give rise to unique nonequilibrium phases of matter without equilibrium analogs. The most prominent example is the realization of discrete time crystals. An intriguing question emerges: What other novel phases can manifest when the constraint of time periodicity is relaxed? In this study, we explore quantum systems subjected to a quasiperiodic drive. Leveraging a strongly interacting spin ensemble in diamond, we identify the emergence of long-lived discrete time quasicrystals. Unlike conventional time crystals, time quasicrystals exhibit robust subharmonic responses at multiple incommensurate frequencies. Furthermore, we show that the multifrequency nature of the quasiperiodic drive allows for the formation of diverse patterns associated with different discrete time quasicrystalline phases. Our findings demonstrate the existence of nonequilibrium phases in quasi-Floquet settings, significantly broadening the catalog of novel phenomena in driven many-body quantum systems.

Exotic phases of matter↗
DOE OSTI2024

Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates

Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

First Search for Dark Sector e+e- Explanations of the MiniBooNE Anomaly at MicroBooNE

The MiniBooNE anomaly has puzzled the neutrino physics community for over two decades. MicroBooNE has previously searched for anomalous electron and photon excesses as potential explanations but the mystery persists. In this poster, we present the first direct test of dark sector models in which dark neutrinos scatter, then decay into e+e− pairs and missing energy, mimicking the MiniBooNE signal. These models have recently emerged as compelling candidates that evade existing constraints. Using 6.87×1020 protons-on-target in the Booster Neutrino Beam, we select forward-going, coherently produced e+e− events in the MicroBooNE detector. We observe 95 events against a constrained background prediction of 69.7±17.3. We set the world's first direct limits on this class of dark sector models, excluding at 95% CL the majority of parameter space viable as a solution to the MiniBooNE anomaly.

Basque, Vincent Marc [Edinburgh U.] (ORCID:0000000↗
NASA NTRS2004

Strategies for Global Optimization of Temporal Preferences

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.

Morris, Paul↗
NASA NTRS2004

Impact of Operating Context on the Use of Structure in Air Traffic Controller Cognitive Processes

This paper investigates the influence of structure on air traffic controllers cognitive processes in the TRACON, En Route, and Oceanic environments. Radar data and voice command analyses were conducted to support hypotheses generated through observations and interviews conducted at the various facilities. Three general types of structure-based abstractions (standard flows, groupings, and critical points) have been identified as being used in each context, though the details of their application varied in accordance with the constraints of the particular operational environment. Projection emerged as a key cognitive process aided by the structure-based abstractions, and there appears to be a significant difference between how time-based versus spatial-based projection is performed by controllers. It is recommended that consideration be given to the value provided by the structure-based abstractions to the controller as well as to maintain consistency between the type (time or spatial) of information support provided to the controller.

Davison, Hayley J.↗
NASA NTRS2018

Exoplanet Biosignatures: Future Directions

We introduce a Bayesian method for guiding future directions for detection of life on exoplanets. We describe empirical and theoretical work necessary to place constraints on the relevant likelihoods, including those emerging from better understanding stellar environment, planetary climate and geophysics, geochemical cycling, the universalities of physics and chemistry, the contingencies of evolutionary history, the properties of life as an emergent complex system, and the mechanisms driving the emergence of life. We provide examples for how the Bayesian formalism could guide future search strategies, including determining observations to prioritize or deciding between targeted searches or larger lower resolution surveys to generate ensemble statistics and address how a Bayesian methodology could constrain the prior probability of life with or without a positive detection.

Bayesian analysis↗
NASA NTRS2011

Two New Pieces of Emergency Response Equipment for use in Confined Space Environments

NASA is developing two new pieces of emergency response equipment that recognize and address the constraints of a confined space environment. One piece of equipment is a respirator designed for use in a post fire environment. Traditional first responders generally use supplied air respirators - they provide cool, dry, safe breathing air to the first responder, and because they are supplied at above ambient pressure, the system is tolerant to a loose-fitting mask. Supplied air respirators have a limited supply of air, but because the traditional first responder intends to address the emergency from outside and then retreat, this limited air supply does not pose a serious problem. NASA uses a supplied oxygen respirator for first response to an emergency affecting air quality on the International Space Station. The air supply is rated for 15 minutes - ISS program managers sponsored a hardware development activity to provide the astronauts up to 8 hours of breathing protection after the supplied air system is exhausted. Size and weight limitations prevent the use of a supplied air system for 8 hours for six crew members. A trade study resulted in the selection of a filtering respirator system over a re-breather system; due to design simplicity, operational simplicity, and likely threats to air quality on ISS. The respirator cartridge that filters smoke particles, adsorbs organics and acid gases, and catalytically converts carbon monoxide to carbon dioxide has been qualified for use on ISS, and was delivered on STS-135, the final mission of the Space Shuttle Program.

Graf, John↗
DOE OSTI2022

The basics of quantum computing for chemists

The rapid and successful strides in quantum chemistry in the past decades can be largely credited to a conspicuous synergy between theoretical and computational advancements. However, the architectural computer archetype that enabled such a progress is approaching a state of more stagnant development. One of the most promising technological avenues for the continuing progress of quantum chemistry is the emerging quantum computing paradigm. This revolutionary proposal comes with several challenges, which span a wide array of disciplines. In chemistry, it implies, among other things, a need to reformulate some of its long established cornerstones in order to adjust to the operational demands and constraints of quantum computers. Due to its relatively recent emergence, much of quantum computing may still seem fairly nebulous and largely unknown to most chemists. It is in this context that here we review and illustrate the basic aspects of quantum information and their relation to quantum computing insofar as enabling simulations of quantum chemistry. As a result, we consider some of the most relevant developments in light of these aspects and discuss the current landscape when of relevance to quantum chemical simulations in quantum computers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

The Challenge of Aviation Emergency and Abnormal Situations

Emergency and abnormal situations occur on flights everyday around the world. They range from minor situations readily managed to extremely serious and highly time-critical situations that deeply challenge the skills of even the most effective crews. How well crews respond to these situations is a function of several interacting sets of issues: (1) the design of non-normal procedures and checklists, (2) design of aircraft systems and automation, (3) specific aspects of the non-normal situation, such as time criticality and complexity of the situation, (4) human performance capabilities and cognitive limitations under high workload and stress, (5) design of training for non-normal situations, (6) philosophies, policies and practices within the industry, and (7) economic and regulatory constraints. Researchers and pilots working on NASA's Emergency and Abnormal Situations project are addressing these issues in a long-range study. In this paper we discuss these issues and illustrate them with examples from recent incidents and accidents.

Burian, Barbara K.↗
DOE OSTI2022

graphenv: a Python library for reinforcement learning on graph search spaces

Many important and challenging problems in combinatorial optimization (CO) can be expressed as graph search problems, in which graph vertices represent full or partial solutions and edges represent decisions that connect them. Graph structure not only introduces strong relational inductive biases for learning (Battaglia et al., 2018) - in this context, by providing a way to explicitly model the value of transitioning (along edges) between one search state (vertex) and the next - but lends itself to problems both with and without clearly defined algebraic structure. For example, classic CO problems on graphs such as the Traveling Salesman Problem (TSP) can be expressed as either pure graph search or integer programs. Other problems, however, such as molecular optimization, do no have concise algebraic formulations and yet are readily implemented as a graph search (V. et al., 2022; Zhou et al., 2019). Such "model-free" problems constitute a large fraction of modern reinforcement learning (RL) research owing to the fact that it is often much easier to write a forward simulation that expresses all of the state transitions and rewards, than to write down the precise mathematical expression of the full optimization problem. In the case of molecular optimization, for example, one can use domain knowledge alongside existing software libraries to model the effect of adding a single bond or atom to an existing but incomplete molecule, and let the RL algorithm build a model of how good a given decision is by "experiencing" the simulated environment many times through. In contrast, a model-based mathematical formulation that fully expresses all the chemical and physical constraints is intractable. In recent years, RL has emerged as an effective paradigm for optimizing searches over graphs and led to state-of-the-art heuristics for games like Go and chess, as well as for classical CO problems such as the TSP. This combination of graph search and RL, while powerful, requires non-trivial software to execute, especially when combining advanced state representations such as Graph Neural Networks (GNN) with scalable RL algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

G-Band Radar Demonstration for Microphysics Field Campaign Report

The G-Band Radar Demonstration for Microphysics (GRDM) campaign took place at the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) from March 15 to April 30, 2024. This was a deployment of two of NASA’s Jet Propulsion Laboratory (JPL) radars and one radar from Brookhaven National Laboratory to demonstrate the utility of high-frequency millimeter-wave radars for remote sensing of stratocumulus microphysical properties. The radars were deployed on the Ellen Browning Scripps Memorial Pier alongside the AMF instruments (Figure 1). The radars include a Ka-band (35 GHz), W-band (94 GHz), and four G-band (158, 165, 174, and 240 GHz) channels. The 240 GHz and W-band channels provide complete Doppler spectra, which are useful for advanced analysis. The 158-175 GHz channels are sensitive to the water vapor profile and are useful for attenuation correction. These radars complement the high-sensitivity ARM KAZR. The goal of the deployment was to observe drizzling stratocumulus and demonstrate the capabilities of the multifrequency radar data set to constrain profiles of liquid water content and drizzle drop characteristic size. The data are still being analyzed. The methodology to derive the cloud and precipitation parameters will exploit differential attenuation and differential reflectivity between low-frequency (Ka-band) and high-frequency (G-band) channels. The method will also exploit the capability of the G-band observations to constrain the attenuation due to water vapor. These observations will quantify the capabilities and limitations of the emerging technology of G-band radars for constraint stratocumulus cloud microphysics, which are key to constraining aerosol-cloud-precipitation interactions and low-cloud climate feedback.

47 OTHER INSTRUMENTATION↗
NASA NTRS1977

Economic Analysis in the Pacific Northwest Land Resources Project: Theoretical Considerations and Preliminary Results

The Pacific Northwest Land Resources Inventory Demonstration Project i s an a ttempt to combine a whole spectrum of heterogeneous geographic, institutional and applications elements in a synergistic approach to the evaluation of remote sensing techniques. This diversity is the prime motivating factor behind a theoretical investigation of alternative economic analysis procedures. For a multitude of reasons--simplicity, ease of understanding, financial constraints and credibility, among others--cost-effectiveness emerges as the most practical tool for conducting such evaluation determinatIons in the Pacific Northwest. Preliminary findings in two water resource application areas suggest, in conformity with most published studies, that Lands at-aided data collection methods enjoy substantial cost advantages over alternative techniques. The pntential for sensitivity analysis based on cost/accuracy tradeoffs is considered on a theoretical plane in the absence of current accuracy figures concerning the Landsat-aided approach.

Morse, D. R. A.↗
NASA NTRS1989

Space 2010

An account is given of the thrust of the NASA-Lewis Research Center's developmental activities in advanced materials for aerospace propulsion and space power systems; these materials must have exceptional strength/weight values, possess high operating temperature capabilities, exhibit long-term property stability, and be affordable within program budgetary constraints. Metal-matrix composites are prominent among emerging materials for space propulsion systems; representative of current interest in this field are the tungsten fiber-reinforced superalloys, which are applicable to liquid rocket propulsion systems' turbomachinery.

Fordyce, J. Stuart↗
NASA NTRS2000

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗
NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗
NASA NTRS2007

Europa Explorer - An Exceptional Mission Using Existing Technology

A mission to Europa has been identified as a high priority by the science community for several years. The difficulty of an orbital mission, primarily due to the propulsive requirements and Jupiter's trapped radiation, led to many studies which investigated various approaches to meeting the science goals. The Europa Orbiter Mission studied in the late 1990's only met the most fundamental science objectives. The science objectives have evolved with the discoveries from the Galileo mission. JPL studied one concept, Europa Explorer, for a Europa orbiting mission which could meet a much expanded set of science objectives. A study science group was formed to verify that the science objectives and goals were being adequately met by the resulting mission design concept. The Europa Explorer design emerged primarily from two key self-imposed constraints: 1) meet the full set of identified nonlander science objectives and 2) use only existing technology.

spacecrafts↗
DOE OSTI2025

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural network (NN) MLIP models is their limited ability to accurately predict the relative energies of systems containing isolated or nearly isolated atoms, which appear in various reactive processes. To address this limitation, we present a mathematical technique for modifying any existing atom-centered NN architecture to account for the energies of isolated atoms. The result produces a consistent prediction of the atomization energy (AE) of a system using minimal constraints on the model. Using this technique, we build a model architecture that we call hierarchically interacting particle neural network (HIP-NN)-AE, an AE-constrained version of the HIP-NN, as well as ANI-AE, the AE-constrained version of the accurate NN engine for molecular energies (ANI). Our results demonstrate AE consistency of AE-constrained models, which drastically improves the AE predictions for the models. We compare the AE-constrained approach to unconstrained models as well as models from the literature in other scenarios, such as bond dissociation energies, bond dissociation pathways, and extensibility tests. These results show that the constraints improve the model performance in some of these tasks and do not negatively affect the performance on any tasks. The AE constraint approach thus offers a robust solution to the challenges posed by isolated atoms in energy prediction tasks.

74 ATOMIC AND MOLECULAR PHYSICS↗