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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Efficiently evaluating loop integrals in the EFTofLSS using QFT integrals with massive propagators

We develop a new way to analytically calculate loop integrals in the Effective Field Theory of Large Scale-Structure. Previous available methods show severe limitations beyond the one-loop power spectrum due to analytical challenges and computational and memory costs. Our new method is based on fitting the linear power spectrum with cosmology-independent functions that resemble integer powers of quantum field theory massive propagators with complex masses. A remarkably small number of them is sufficient to reach enough accuracy. Similarly to former approaches, the cosmology dependence is encoded in the coordinate vector of the expansion of the linear power spectrum in our basis. We first produce cosmology-independent tensors where each entry is the loop integral evaluated on a given combination of basis vectors. For each cosmology, the evaluation of a loop integral amounts to contracting this tensor with the coordinate vector of the linear power spectrum. The 3-dimensional loop integrals for our basis functions can be evaluated using techniques familiar to particle physics, such as recursion relations and Feynman parametrization. We apply our formalism to evaluate the one-loop bispectrum of galaxies in redshift space. The final analytical expressions are quite simple and can be evaluated with little computational and memory cost. We show that the same expressions resolve the integration of all one-loop N-point function in the EFTofLSS. This method, which is originally presented here, has already been applied in the first one-loop bispectrum analysis of the BOSS data to constraint ΛCDM parameters and primordial non-Gaussianities [1, 2].

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy

We present OrbNet Denali, a machine learning model for an electronic structure that is designed as a drop-in replacement for groundstate density functional theory (DFT) energy calculations. The model is a message-passing graph neural network that uses symmetryadapted atomic orbital features from a low-cost quantum calculation to predict the energy of a molecule. OrbNet Denali is trained on a vast dataset of 2.3 × 10 6 DFT calculations on molecules and geometries. This dataset covers the most common elements in biochemistry and organic chemistry (H, Li, B, C, N, O, F, Na, Mg, Si, P, S, Cl, K, Ca, Br, and I) and charged molecules. OrbNet Denali is demonstrated on several well-established benchmark datasets, and we find that it provides accuracy that is on par with modern DFT methods while offering a speedup of up to three orders of magnitude. For the GMTKN55 benchmark set, OrbNet Denali achieves WTMAD-1 and WTMAD-2 scores of 7.19 and 9.84, on par with modern DFT functionals. For several GMTKN55 subsets, which contain chemical problems that are not present in the training set, OrbNet Denali produces a mean absolute error comparable to those of DFT methods. For the Hutchison conformer benchmark set, OrbNet Denali has a median correlation coefficient of R 2 = 0.90 compared to the reference DLPNO-CCSD(T) calculation and R 2 = 0.97 compared to the method used to generate the training data (ωB97X-D3/def2- TZVP), exceeding the performance of any other method with a similar cost. Similarly, the model reaches chemical accuracy for noncovalent interactions in the S66x10 dataset. For torsional profiles, OrbNet Denali reproduces the torsion profiles of ωB97X-D3/def2-TZVP with an average mean absolute error of 0.12 kcal/mol for the potential energy surfaces of the diverse fragments in the TorsionNet500 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Electrochemical Oxidation and Functionalization of Low‐Density Polyethylene

Abstract Plastic waste is a serious environmental issue, and polyethylene (PE) is a significant component. The chemically inert nature of PE makes its recycling/upcycling process challenging. Thus, a novel method was demonstrated that enables the selective electrochemical functionalization and deconstruction of low‐density polyethylene (LDPE) by using low‐cost transition metal electrocatalysts at room temperature (23±2 °C) and low cell voltage (±1 V). Three different electrode and electrolyte combinations were studied for the oxidation of LDPE: copper metal/copper (II) ions, nickel metal/nickel (II) ions, and stainless steel/iron (II) and (III) ions. The copper and nickel electrode/electrolyte pairs showed a promising capability for oxidation and chain‐scission of LDPE. In contrast, the stainless‐steel and iron electrode/electrolyte pair showed no activity towards LDPE oxidation or depolymerization. The electrolysis of LDPE offers a new vista for the depolymerization and upcycling of plastics, further understanding of the process is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Range‐separated density functional theory using multiresolution analysis and quantum computing

Quantum computers are expected to outperform classical computers for specific problems in quantum chemistry. Such calculations remain expensive, but costs can be lowered through the partition of the molecular system. In the present study, partition was achieved with range-separated density functional theory (RS-DFT). The use of RS-DFT reduces both the basis set size and the active space size dependence of the ground state energy in comparison with the use of wave function theory (WFT) alone. The utilization of pair natural orbitals (PNOs) in place of canonical molecular orbitals (MOs) results in more compact qubit Hamiltonians. To test this strategy, a basis-set independent framework, known as multiresolution analysis (MRA), was employed to generate PNOs. Tests were conducted with the variational quantum eigensolver for a number of molecules. The results show that the proposed approach reduces the number of qubits needed to reach a target energy accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

A Multi-Purpose Modular Electronics Integration Node for Exploration Extravehicular Activity

As NASA works to develop an effective integrated portable life support system design for exploration Extravehicular activity (EVA), alternatives to the current system s electrical power and control architecture are needed to support new requirements for flexibility, maintainability, reliability, and reduced mass and volume. Experience with the current Extravehicular Mobility Unit (EMU) has demonstrated that the current architecture, based in a central power supply, monitoring and control unit, with dedicated analog wiring harness connections to active components in the system has a significant impact on system packaging and seriously constrains design flexibility in adapting to component obsolescence and changing system needs over time. An alternative architecture based in the use of a digital data bus offers possible wiring harness and system power savings, but risks significant penalties in component complexity and cost. A hybrid architecture that relies on a set of electronic and power interface nodes serving functional models within the Portable Life Support System (PLSS) is proposed to minimize both packaging and component level penalties. A common interface node hardware design can further reduce penalties by reducing the nonrecurring development costs, making miniaturization more practical, maximizing opportunities for maturation and reliability growth, providing enhanced fault tolerance, and providing stable design interfaces for system components and a central control. Adaptation to varying specific module requirements can be achieved with modest changes in firmware code within the module. A preliminary design effort has developed a common set of hardware interface requirements and functional capabilities for such a node based on anticipated modules comprising an exploration PLSS, and a prototype node has been designed assembled, programmed, and tested. One instance of such a node has been adapted to support testing the swingbed carbon dioxide and humidity control element in NASA s advanced PLSS 2.0 test article. This paper will describe the common interface node design concept, results of the prototype development and test effort, and plans for use in NASA PLSS 2.0 integrated tests.

Hodgson, Edward↗
NASA NTRS1975

Fixed-range optimum trajectories for short-haul aircraft

An algorithm, based on the energy-state method, is derived for calculating optimum trajectories with a range constraint. The basis of the algorithm is the assumption that optimum trajectories consist of, at most, three segments: an increasing energy segment (climb); a constant energy segment (cruise); and a decreasing energy segment (descent). This assumption allows energy to be used as the independent variable in the increasing and decreasing energy segments, thereby eliminating the integration of a separate adjoint differential equation and simplifying the calculus of variations problem to one requiring only pointwise extremization of algebraic functions. The algorithm is used to compute minimum fuel, minimum time, and minimum direct-operating-cost trajectories, with range as a parameter, for an in-service CTOL aircraft and for an advanced STOL aircraft. For the CTOL aircraft and the minimum-fuel performance function, the optimum controls, consisting of air-speed and engine power setting, are continuous functions of the energy in both climb and descent as well as near the maximum or cruise energy. This is also true for the STOL aircraft except in the descent where at one energy level a nearly constant energy dive segment occurs, yielding a discontinuity in the airspeed at that energy. The reason for this segment appears to be the relatively high fuel flow at idle power of the engines used by this STOL aircraft. Use of a simplified trajectory which eliminates the dive increases the fuel consumption of the total descent trajectory by about 10 percent and the time to fly the descent by about 19 percent compared to the optimum.

Erzberger, H.↗
DOE OSTI2024

Modeling with uncertainty quantification reveals the essentials of a non-canonical algal carbon-concentrating mechanism

The thermoacidophilic red alga Cyanidioschyzon merolae survives its challenging environment likely in part by operating a carbon-concentrating mechanism (CCM). Here, we demonstrated that C. merolae 's cellular affinity for CO 2 is stronger than the affinity of its rubisco for CO 2 . This finding provided additional evidence that C. merolae operates a CCM while lacking the structures and functions characteristic of CCMs in other organisms. To test how such a CCM could function, we created a mathematical compartmental model of a simple CCM, distinct from those we have seen previously described in detail. The results of our modeling supported the feasibility of this proposed minimal and non-canonical CCM in C. merolae . To facilitate the robust modeling of this process, we measured and incorporated physiological and enzymatic parameters into the model. Additionally, we trained a surrogate machine-learning model to emulate the mechanistic model and characterized the effects of model parameters on key outputs. This parameter exploration enabled us to identify model features that influenced whether the model met the experimentally derived criteria for functional carbon concentration and efficient energy usage. Such parameters included cytosolic pH, bicarbonate pumping cost and kinetics, cell radius, carboxylation velocity, number of thylakoid membranes, and CO 2 membrane permeability. Our exploration thus suggested that a non-canonical CCM could exist in C. merolae and illuminated the essential features generally necessary for CCMs to function.

Steensma, Anne K. [Michigan State Univ., East Lans↗
NASA NTRS1975

Space Tug Avionics Definition Study. Volume 5: Cost and Programmatics

The baseline avionics system features a central digital computer that integrates the functions of all the space tug subsystems by means of a redundant digital data bus. The central computer consists of dual central processor units, dual input/output processors, and a fault tolerant memory, utilizing internal redundancy and error checking. Three electronically steerable phased arrays provide downlink transmission from any tug attitude directly to ground or via TDRS. Six laser gyros and six accelerometers in a dodecahedron configuration make up the inertial measurement unit. Both a scanning laser radar and a TV system, employing strobe lamps, are required as acquisition and docking sensors. Primary dc power at a nominal 28 volts is supplied from dual lightweight, thermally integrated fuel cells which operate from propellant grade reactants out of the main tanks.

Source record↗
NASA NTRS2008

FIDO-Class Development Rover

A report describes a rover-type robotic wheeled vehicle recently built for use as a testbed for development of software for future rover-type vehicles. This vehicle is a derivative of the Field Integrated Design and Operations (FIDO) rover, which is a prototype Mars-exploration rover that also serves as a terrestrial testbed. The present vehicle was designed to be nearly functionally identical to the FIDO rover but to be built at much lower cost and to incorporate several improvements to increase utility for development work. Accordingly, considerable effort was made to use commercial off-the-shelf parts and other parts that could be fabricated easily and at low cost. Important features of this vehicle include six-wheel drive and six-wheel steering; onboard computer and power, control, and data-communication electronics having flexibility needed for development of software; significantly increased maximum speed (60 cm/s versus 6 cm/s for the FIDO rover); a rocker-bogey suspension with external differential link, functionally equivalent to that of the FIDO rover; and a hand-held remote controller that can be used to control vehicle motion manually without using the computer (or while waiting for the onboard computer to boot up).

Herman, Herman↗
DOE OSTI2023

Rationally Engineered Vertically Aligned β ‐Ga 2− x W x O 3 Nanocomposites for Self‐Biased Solar‐Blind Ultraviolet Photodetectors with Ultrafast Response

Abstract With the astonishing advancement of present technology and increasing energy consumption, there is an ever‐increasing demand for energy‐efficient multifunctional sensors or transducers based on low‐cost, eco‐friendly material systems. In this context, self‐assembled vertically aligned β ‐Ga 2− x W x O 3 nanocomposite (GWO‐VAN) architecture‐assisted self‐biased solar‐blind UV photodetection on a silicon platform, which is the heart of traditional electronics is presented. Utilizing precisely controlled growth parameters, the formation of W‐enriched vertical β ‐Ga 2− x W x O 3 nanocolumns embedded into the W‐deficient β ‐Ga 2− x W x O 3 matrix is reached. Detailed structural and morphological analyses evidently confirm the presence of β ‐Ga 2− x W x O 3 nanocomposite with a high structural and chemical quality. Furthermore, absorption and photoluminescence spectroscopy explains photo‐absorption dynamics and the recombination through possible donor–acceptor energy states. The proposed GWO‐VAN framework facilitates evenly dispersed nanoregions with asymmetric donor energy state distribution and thus forms build‐in potential at the vertical β ‐Ga 2− x W x O 3 interfaces. As a result, the overall heterostructure evinces photovoltaic nature under the UV irradiation. A responsivity of ≈30 A/W is observed with an ultrafast response time (≈350 µs) under transient triggering conditions. Corresponding detectivity and external quantum efficiency are 7.9 × 10 12 Jones and 1.4 × 10 4 %, respectively. It is believed that, while this is the first report exploiting GWO‐VAN architecture to manifest self‐biased solar‐blind UV photodetection, the implication of the approach is enormous in designing electronics for extreme environment functionality and has immense potential to demonstrate drastic improvement in low‐cost UV photodetector technology.

Das, Debabrata↗
DOE OSTI2022

Time-dependent density functional theory of charge, energy, and spin transport, and quantum continuum mechanics (Final Report)

The overarching goal of this project, which unfolded over a period of seventeen years, including two no-cost extensions in the last two years, was to extend and deepen our ability to use time-dependent density functional theory and related theoretical methods for the description of the transport of charge, spin, or energy in quantum electronic systems at the nanoscale. The output of our efforts is contained in 52 papers, listed below, which we have published since 2006. There have also been many presentations at international conferences, workshops, colloquia and seminars. This body of work has been carried out with the essential input of 8 postdoctoral students (who were supported by the grant) and several external senior collaborators and their postdocs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Ab Initio Modeling of Aqueous Methanol Mixtures at DFT-SCAN Level Using Machine Learning Interatomic Potentials

Abstract Methanol–water mixtures find use in many applications, particularly catalytic energy conversion processes. Their importance has motivated numerous computational studies, most of which employed molecular dynamics based on classical force fields. These enable simulations of large systems on long time scales but do not reliably describe reactive dynamics involving bond breaking and bond formation. In contrast, ab initio molecular dynamics (AIMD) based on density functional theory (DFT) is generally more reliable for such applications but has a high computational cost, which discourages systematic studies of alcohol-water mixtures. To remedy this, we trained a machine learning interatomic potential capable of probing the properties of aqueous methanol mixtures at the DFT level using the SCAN functional. Our results show that SCAN qualitatively reproduces multiple key experimental features arising from the amphiphilic nature of methanol, including density, diffusion coefficients, X-ray structure factors, and Kirkwood–Buff integrals. We also find that structural correlations between water molecules are somewhat overestimated, leading to a stronger preferential association than that predicted by experiments. However, increasing the temperature by 30 K mitigates this effect and also recovers the correct mobilities of both methanol and water. These results indicate that SCAN provides an accurate description of methanol–water mixtures, making it a reliable choice for investigating the reactive dynamics in such systems.

Park, Sanghyun J. [Princeton University , , , ,]↗
NASA NTRS1977

Cost benefit analysis of the transfer of NASA remote sensing technology to the state of Georgia

The author has identified the following significant results. First order benefits can generally be quantified, thus allowing quantitative comparisons of candidate land cover data systems. A meaningful dollar evaluation of LANDSAT can be made by a cost comparison with equally effective data systems. Users of LANDSAT data can be usefully categorized as performing three general functions: planning, permitting, and enforcing. The value of LANDSAT data to the State of Georgia is most sensitive to the parameters: discount rate, digitization cost, and photo acquisition cost. Under a constrained budget, LANDSAT could provide digitized land cover information roughly seven times more frequently than could otherwise be obtained. Thus on one hand, while the services derived from LANDSAT data in comparison to the baseline system has a positive net present value, on the other hand if the budget were constrained, more frequent information could be provided using the LANDSAT system than otherwise be obtained.

Zimmer, R. P.↗
NASA NTRS1984

Evaluating software testing strategies

The strategies of code reading, functional testing, and structural testing are compared in three aspects of software testing: fault detection effectiveness, fault detection cost, and classes of faults detected. The major results are the following: (1) Code readers detected more faults than did those using the other techniques, while functional tester detected more faults than did structural testers; (2) Code readers had a higher fault detection rate than did those using the other methods, while there was no difference between functional testers and structural testers; (3) Subjects testing the abstract data type detected the most faults and had the highest fault detection rate, while individuals testing the database maintainer found the fewest faults and spent the most effort testing; (4) Subjects of intermediate and junior expertise were not different in number or percentage of faults found, fault detection rate, or fault detection effort; (5) subjects of advanced expertise found a greater number of faults than did the others, found a greater percentage of faults than did just those of junior expertise, and were not different from the others in either fault detection rate or effort; and (6) Code readers and functional testers both detected more omission faults and more control faults than did structural testers, while code readers detected more interface faults than did those using the other methods.

Selby, R. W., Jr.↗
NASA NTRS1996

High-Lift Systems on Commercial Subsonic Airliners

The early breed of slow commercial airliners did not require high-lift systems because their wing loadings were low and their speed ratios between cruise and low speed (takeoff and landing) were about 2:1. However, even in those days the benefit of high-lift devices was recognized. Simple trailing-edge flaps were in use, not so much to reduce landing speeds, but to provide better glide-slope control without sideslipping the airplane and to improve pilot vision over the nose by reducing attitude during low-speed flight. As commercial-airplane cruise speeds increased with the development of more powerful engines, wing loadings increased and a real need for high-lift devices emerged to keep takeoff and landing speeds within reasonable limits. The high-lift devices of that era were generally trailing-edge flaps. When jet engines matured sufficiently in military service and were introduced commercially, airplane speed capability had to be increased to best take advantage of jet engine characteristics. This speed increase was accomplished by introducing the wing sweep and by further increasing wing loading. Whereas increased wing loading called for higher lift coefficients at low speeds, wing sweep actually decreased wing lift at low speeds. Takeoff and landing speeds increased on early jet airplanes, and, as a consequence, runways worldwide had to be lengthened. There are economical limits to the length of runways; there are safety limits to takeoff and landing speeds; and there are speed limits for tires. So, in order to hold takeoff and landing speeds within reasonable limits, more powerful high-lift devices were required. Wing trailing-edge devices evolved from plain flaps to Fowler flaps with single, double, and even triple slots. Wing leading edges evolved from fixed leading edges to a simple Krueger flap, and from fixed, slotted leading edges to two- and three-position slats and variable-camber (VC) Krueger flaps. The complexity of high-lift systems probably peaked on the Boeing 747, which has a VC Krueger flap and triple-slotted, inboard and outboard trailing-edge flaps. Since then, the tendency in high-lift system development has been to achieve high levels of lift with simpler devices in order to reduce fleet acquisition and maintenance costs. The intent of this paper is to: (1) review available high-lift devices, their functions, and design criteria; (2) appraise high-lift systems presently in service on commercial air liners; (3) present personal study results on high-lift systems; (4) develop a weight and cost model for high-lift systems; and (5) discuss the development tendencies of future high-lift systems.

Rudolph, Peter K. C.↗
DOE OSTI2020

Accelerating Finite-temperature Kohn-Sham Density Functional Theory\ with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerating Finite-Temperature Kohn-Sham Density Functional Theory with Deep Neural Networks

We present a numerical modeling workflow based on machine learning (ML) which reproduces the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible computational cost. Based on deep neural networks, our workflow yields the local density of states (LDOS) for a given atomic configuration. From the LDOS, spatially-resolved, energy-resolved, and integrated quantities can be calculated, including the DFT total free energy, which serves as the Born-Oppenheimer potential energy surface for the atoms. We demonstrate the efficacy of this approach for both solid and liquid metals and compare results between independent and unified machine-learning models for solid and liquid aluminum. Our machine-learning density functional theory framework opens up the path towards multiscale materials modeling for matter under ambient and extreme conditions at a computational scale and cost that is unattainable with current algorithms.

97 MATHEMATICS AND COMPUTING↗