SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
BEEM spectroscopy and imaging have been applied to the Au/GaN interface. In contrast to previous BEEM measurements, spectra yield a Schottky barrier height of 1.04eV that agrees well with the highest values measured by conventional methods.
An apparatus that passes vibrational energy across a mechanical structure lacking a perforation. The disclosed apparatus and method provide the ability to transfer work (rotary or linear motion) across pressure or thermal barriers or in a sterile environment without generating contaminants; the presence of reflectors in the solid barrier to enhance the efficiency of the energy/power transmission, and the ability to produce a bi-directional driving mechanism using a plurality of different mode resonances, such as a fundamental frequency resonance and a higher frequency resonance. In some instances, a plane within the mechanical structure lacking a perforation is a nodal plane of the vibrational energy field.
As humanity expands its ventures into lunar and planetary exploration, the demand intensifies for resilient materials capable of enduring extreme environmental and service conditions. The Moon’s surface presents numerous challenges, including ultra-high vacuum exposure, temperature extremes and intense radiation. Additionally, lunar regolith poses a significant threat to component durability and reusability due to its abrasive nature. Lunar dust particles scoring, adhering, or embedding into surfaces and within device-confined geometries, such as bearings, drive mechanisms and connectors, can cause premature component wear or failure. Furthermore, the interaction between the rocket plume and the surface during vehicle landings and ascents creates severe erosive conditions near critical vehicle components and adjacent infrastructure. A key barrier hindering materials discovery for lunar dust tolerant applications is a lack of standard laboratory methods to evaluate material properties and performance under representative operating conditions. A case will be presented for research activities supporting identification, processing and characterization of candidate materials in conjunction with innovations in standardized testing and qualification. Results will highlight current and emerging test methods for simulating lunar dust exposure and component degradation, paving the way for a new generation of robust materials and coatings for space exploration.
As humanity expands its ventures into lunar exploration, the demand intensifies for materials capable of enduring extreme environmental and service conditions. The Moon’s surface presents numerous challenges, including ultra-high vacuum exposure, temperature extremes and intense radiation. Additionally, lunar regolith threatens component durability and reusability due to its abrasive nature. Lunar dust particles scoring, adhering or embedding into surfaces and within device-confined geometries, such as bearings, drive mechanisms and connectors, can cause premature component wear or failure. Furthermore, the interaction between the rocket plume and surface during vehicle landings and ascents creates severe erosive conditions near critical vehicle components and adjacent infrastructure. A key barrier hindering materials discovery for lunar dust tolerant applications is a lack of standard laboratory methods to evaluate material properties and performance under representative operating conditions. A case will be presented for research activities supporting identification, processing and characterization of candidate materials in conjunction with innovations in standardized testing and qualification. Results will highlight current and emerging test methods for simulating lunar dust exposure and component degradation, paving the way for a new generation of robust materials and coatings for space exploration.
Heating, ventilation, and air-conditioning (HVAC) systems consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. commercial buildings. Additionally, commercial refrigeration (R) systems add about 1 quad to commercial buildings energy consumption. Most HVAC systems operate with one or more faults that result in increased energy consumption. Fault detection and diagnostics (FDD) tools have been developed to address this national issue, and many tools are commercially available. FDD tools have the potential to save considerable energy for an existing commercial rooftop unit (RTU) and refrigeration systems. These devices can be used for both retro commissioning and, when faults are addressed, continuous commissioning. However, there appears to be multiple market barriers for this technology. Although there are efforts to develop FDD tool standards, currently there are no standards and methods to define functions, capabilities, accuracy, and reliability of FDD tools in the field. Moreover, most of the commercial FDD tools have not been verified in the field independently. This paper presents a comprehensive approach for bringing HVAC FDD tools into the mainstream. The approach involves demonstrating ten commercially available FDD tools installed at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying and assessing market barriers, creating a process evaluation methodology, and assisting utility companies in developing incentive programs. Furthermore, the preliminary baseline results from the case study demonstrate how the use of an independent monitoring system (IMS) can be used for ground-truth in evaluating FDD tools in the field.
Accurate rate constants are crucial for understanding and optimizing catalytic reactions mediated by enzymes, metalloproteins, and heterogeneous catalysts. These systems frequently present a dual computational challenge. Multiconfigurational reaction sites require multireference techniques for the accurate treatment of the electronic structure, and high activation barriers prevent efficient sampling of unbiased reactive transitions. In this work, we combine multiconfiguration pair-density functional theory (MC-PDFT) as an accurate and efficient multireference electronic structure method with on-the-fly probability-enhanced sampling flooding (OPESf) as an enhanced sampling method capable of accelerating reactive transitions. We demonstrate the approach on the Diels–Alder [4+2] cycloaddition between cis-butadiene and ethene as a reaction characterized by a large activation barrier and multireference character. MC-PDFT–OPESf provides reaction rates in agreement with experiments at a fraction of the computational cost required by conventional unbiased ab initio calculations. Here, we propose MC-PDFT–OPESf as an efficient approach for computing kinetics in strongly correlated molecular systems.
Microbiomes are essential to a host’s physiology and health. Despite the overall importance of microbiomes to animal health, they remain understudied in wildlife. Microbiomes function as physical barriers to invading pathogens, and changes in the diversity or composition of microbes within a host may disrupt this barrier. In order to use microbiomes in wildlife ecology, knowledge of the natural variation within and among species is essential. We compare the diversity and composition of two avian species that share the same habitat and niche in our study area, the western screech-owl (Megascops kennicottii) and the whiskered screech-owl (M. trichopsis). We used a targeted 16S sequencing method to improve the taxonomic resolution of microbiomes. We found similar measures of alpha diversity between species and sample types (cloacal samples vs. fecal samples). However, there were significant differences in bacterial species richness among nestlings from different nest boxes, and the composition differed between the two bird species and among nestlings from different nest boxes. Western screech-owls had more variation in alpha diversity and composition and had fewer bacterial species in their core microbiome than whiskered screech-owls. Siblings are likely to yield similar findings for microbiomes; thus, sampling nestlings from different nests may be most informative for monitoring population-level changes.
The ability to deterministically fabricate nanoscale architectures with atomic precision is the central goal of nanotechnology, whereby highly localized changes in the atomic structure can be exploited to control device properties at their fundamental physical limit. Here, an automated, feedback-controlled atomic fabrication method is reported and the formation of 1D–2D heterostructures in MoS 2 is demonstrated through selective transformations along specific crystallographic orientations. The atomic-scale probe of an aberration-corrected scanning transmission electron microscope (STEM) is used, and the shape and symmetry of the scan pathway relative to the sample orientation are controlled. The focused and shaped electron beam is used to reliably create Mo 6 S 6 nanowire (MoS-NW) terminated metallic-semiconductor 1D–2D edge structures within a pristine MoS 2 monolayer with atomic precision. From these results, it is found that a triangular beam path aligned along the zig-zag sulfur terminated (ZZS) direction forms stable MoS-NW edge structures with the highest degree of fidelity without resulting in disordering of the surrounding MoS 2 monolayer. Density functional theory (DFT) calculations and ab initio molecular dynamic simulations (AIMD) are used to calculate the energetic barriers for the most stable atomic edge structures and atomic transformation pathways. These discoveries provide an automated method to improve understanding of atomic-scale transformations while opening a pathway toward more precise atomic-scale engineering of materials.
The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Here, our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.
The promise of active learning is to reduce the number of labeled examples required by supervised machine learning algorithms. The largest potential benefits lie in entirely new domains, for which no labeled examples yet exist. Yet to date, most active learning studies are retroactive and demonstrate the benefits that could have been gained if active learning had been used. What are the barriers to true adoption and utilization of active learning? We focus on two: (1) the cold start or class discovery problem, in which active learning methods may struggle to make progress with zero labeled examples, and (2) the cost of having the classifier in the loop to select the next example to be labeled. We assess different active learning approaches in the context of these two barriers and conclude with recommendations for how to employ active learning in new domains. As an example, we report on the use of active learning on a large, novel data set of Mars surface images.
The shapes and elevations of barrier islands may change dramatically over a short period of time during a storm. Coastal scientists and engineers, however, are currently unable to measure these changes occurring over an entire barrier island at once. This three-year project, which is funded by NASA and jointly conducted by the Bureau of Economic Geology and the Center for Space Research at The University of Texas at Austin, is designed to overcome this problem by developing the use of interferometry from airborne synthetic aperture radar (AIRSAR) to measure coastal topography and to detect storm-induced changes in topography. Surrogate measures of topography observed in multiband, fully polarimetric AIRSAR (This type of data are now referred to as POLSAR data.) are also being investigated. Digital elevation models (DEM) of Galveston Island and Bolivar Peninsula, Texas obtained with Topographic SAR (TOPSAR) are compared with measurements by Global Positioning System (GPS) ground surveys and electronic total station surveys. In addition to topographic mapping, this project is evaluating the use of POLSAR to detect old features such as storm scarps, storm channels, former tidal inlets, and beach ridges that have been obscured by vegetation, erosion, deposition, and artificial filling. We have also expanded the work from the original proposal to include the mapping of coastal wetland vegetation and depositional environments. Methods developed during this project will provide coastal geologists with an unprecedented tool for monitoring and understanding barrier island systems. This understanding will improve overall coastal management policies and will help reduce the effects of natural and man-induced coastal hazards. This report summarizes our accomplishments during the second year of the study. Also included is a discussion of our planned activities for year 3 and a revised budget.
Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.
We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.
In its mission to expand knowledge and improve aviation, NASA conducts research to address sonic boom noise, the prime barrier to overland supersonic flight. NASA is currently preparing for a community survey campaign to assess response to noise from the new X-59 aircraft. During each community survey, a substantial number of observations must be collected over a limited timeframe to generate a dose response relationship. A sample of residents will be recruited in advance to fill out a brief survey each time X-59 flies over, approximately 80 times throughout a month. In preparation NASA conducted a month-long test of survey methods in 2023. A sample of 800 residents was recruited from a simulated fly-over area. Because there were no actual X-59 fly-overs, respondents were asked about their reactions to noise from normal aircraft operations. The respondents chose whether to fill out the survey on the web or via a smartphone application. Evaluating response rates and how they evolved over time was a specific focus of the test. Also, a graduated incentive structure was implemented to keep respondents engaged. Finally, location data was collected from respondents since it will be needed to estimate individual noise exposure from X-59. The results of this survey test will help determine the design of the community survey campaign.
Silicon (Si)-based materials are one of the most promising anodes to be applied in rechargeable lithium ion batteries. However, the active Si/electrolyte interface causes continuous side reactions and poor conductivity, which significantly decreases the cycling stability. Cu is the only metallic current collector that has been known to promote electron conduction and lithium-ion transfer without alloying reaction occurrence. However, to the best current knowledge, scalable interface engineering incorporating Cu has not been reported. In this study, this conductive Cu interface (CCI) is constructed through a self-assembly carbothermic reduction method to achieve efficient protection of Si/electrolyte interfaces while allowing for fast Li + diffusion. The energy barrier of lithium-ion diffusion through Cu is calculated to be 0.1965 eV, which is much lower than that through Au, Fe, and Ni films. Benefiting from the enhanced interfacial protection and kinetics of Si with CCI, a fading rate of only 0.068% is maintained for 1000 cycles and an aerial capacity of 4.78 mAh cm -2 is achieved after 280 cycles, which is comparable to the industry standards required for practical application.
Oxiranes are a class of cyclic ethers formed in abundance during low-temperature combustion of hydrocarbons and biofuels, either via chain-propagating steps that occur from unimolecular decomposition of β -hydroperoxyalkyl radicals ( β -˙QOOH) or from reactions of HOÓ with alkenes. Ethyloxirane is one of four alkyl-substituted cyclic ether isomers produced as an intermediate from n -butane oxidation. While rate coefficients for β -˙QOOH → ethyloxirane + ÓH are reported extensively, subsequent reaction mechanisms of the cyclic ether are not. As a result, chemical kinetics mechanisms commonly adopt simplified chemistry to describe ethyloxirane consumption by convoluting several elementary reactions into a single step, which may introduce mechanism truncation error—uncertainty derived from missing or incomplete chemistry. Here we provide fundamental insight on reaction mechanisms of ethyloxirane in support of ongoing efforts to minimize mechanism truncation error. Reaction mechanisms are inferred from the detection of products during chlorine atom-initiated oxidation experiments using multiplexed photoionization mass spectrometry conducted at 10 Torr and temperatures of 650 K and 800 K. To complement the experiments, calculations of stationary point energies were conducted using the ccCA-PS3 composite method on ˙R + O 2 potential energy surfaces for the four ethyloxiranyl radical isomers, which produced barrier heights for 24 reaction pathways. In addition to products from ˙QOOH → cyclic ether + ÓH and ˙R + O 2 → conjugate alkene + HOÓ, both of which were significant pathways and are prototypical to alkane oxidation, other species were identified from ring-opening of both ethyloxiranyl and ˙QOOH radicals. The latter occurs when the unpaired electron is localized on the ether group, causing the initial ˙QOOH structure to ring-open and form a resonance-stabilized ketohydroperoxide-type radical. The present work provides the first analysis of ethyloxirane oxidation chemistry, which reveals that consumption pathways are complex and may require an expansion of submechanisms to increase the fidelity of chemical kinetics mechanisms.
The presence of chemically different and compositionally varying plastics in mixed postconsumer recovered plastic (PCR) presents daunting barriers to recycling and upcycling efforts. This review systematically outlines how different processing techniques and characterization methods can be implemented to improve PCR's mechanical recycling and upcycling processes. The review further addresses the recycling challenges in the processing of mixed plastics from PCR and how their mechanical properties can be enhanced by making use of different types of compatibilizers such as copolymers, Janus nanoparticles as well as different approaches such as solid-state pulverization and microfibrillarization. In addition, the state-of-the-art applications of recycled plastics usage in automotive and construction are reviewed.
Introduction: Despite the plethora of research devoted to analyzing the impact of disability on travel behavior, not enough studies have investigated the varying impact of social and environmental factors on the mode choice of people with disabilities that restrict their ability to use transportation modes efficiently. This research gap can be addressed by investigating the factors influencing the mode choice behavior of people with travel-limiting disabilities, which can inform the development of accessible and sustainable transportation systems. Additionally, such studies can provide insights into the social and economic barriers faced by this population group, which can help policymakers to promote social inclusion and equity. Method: This study utilized a Random Parameters Logit model to identify the individual, trip, and environmental factors that influence mode selection among people with travel-limiting disabilities. Here, using the 2017 National Household Travel Survey data for New York State, which included information on respondents with travel-limiting disabilities, the analysis focused on a sample of 8,016 people. In addition, climate data from the National Oceanic and Atmospheric Administration were integrated as additional explanatory variables in the modeling process. Results: The results revealed that people with disabilities may be inclined to travel longer distances walking in the absence of suitable accommodation facilities for other transportation modes. Furthermore, people were less inclined to walk during summer and winter, indicating a need to consider weather conditions as a significant determinant of mode choice. Moreover, low-income people with disabilities were more likely to rely on public transport or walking. Conclusion: Based on this study’s findings, transportation agencies could design infrastructure and plan for future expansions that is more inclusive and accessible, thus catering to the mobility needs of people with travel-limiting disabilities.