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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 325 records · Page 18

A shared-mobility-based framework for evacuation planning and operations under forecast uncertainty

To meet evacuation needs from carless populations who need personalized assistance to evacuate safely, in this article we propose a ridesharing-based evacuation program that recruits volunteer drivers before a disaster strikes, and then matches volunteer drivers with evacuees once demand is realized. Here we optimize resource planning and evacuation operations under uncertain spatiotemporal demand, and construct a two-stage stochastic mixed-integer program to ensure high demand fulfillment rates. We consider three formulations to improve the number of evacuees served, by minimizing an expected penalty cost, imposing a probabilistic constraint, and enforcing a constraint on the conditional value at risk of the total number of unserved evacuees, respectively. We discuss the benefits and disadvantages of the different risk measures used in the three formulations, given certain carless population sizes and the variety of evacuation modes available. We also develop a heuristic approach to provide quick, dynamic and conservative solutions. We demonstrate the performance of our approaches using five different networks of varying sizes based on regions of Charleston County, South Carolina, an area that experienced a mandatory evacuation order during Hurricane Florence, and utilize real demographic data and hourly traffic count data to estimate the demand distribution.

97 MATHEMATICS AND COMPUTING↗

cuAlign: Scalable Network Alignment on GPU Accelerators

Given two graphs, the objective of network alignment is to find the best one-to-one mapping of vertices in one graph (??) to vertices in the other (??), such that the number of overlaps is maximized. We say that edges(??, ??) ???and(??', ??') ??? are overlapped if ?? is mapped to ??' and ?? is mapped to??'. Network alignment is an important optimization problem with several applications in bioinformatics, computer vision and ontology matching. Since it is an NP-hard problem, efficient heuristics and scalable implementations are necessary. In this work, we introduce a new framework that combines the concepts of intra-network proximity using vertex embedding,Belief Propagation (BP) and approximate weighted matching, and provides qualitative improvements up to22%over state-of-the-art approaches. We also provide scalable implementations on GPU accelerators, demonstrating up to19×speedup for Belief Propagation and 3× speedup for approximate weighted matching relative to previous multithreaded implementation. A combination of combinatorial and algebraic kernels within the network alignment algorithm poses significant hurdles for parallelization. Load imbalance and irregular DRAM traffic limit achievable performance on GPUs. Our novel approach identifies and exploits unique structural proper-ties of the BP-based algorithm and employs code fusion to reduce data movement between different steps of the algorithm. Using a diverse set of inputs, we demonstrate qualitative improvements of our algorithms, and performance gains of our GPU-accelerated implementation. We believe that our work will enable algorithmic improvements and practical applications of network alignment.

Xiang, Lizhi↗

A three solar cell system based on a self-supporting, transparent AlGaAs top solar cell

Development of a three solar cell stack can lead to practical efficiencies greater than 30 percent (1x,AM0). A theoretical efficiency limitation of 43.7 percent at AM0 and one sun is predicted by this model. Including expected losses, a practical system efficiency of 36.8 percent is anticipated. These calculations are based on a 1.93eV/1.43eV/0.89eV energy band gap combination. AlGaAs/GaAs/GaInAsP materials can be used with a six-terminal wiring configuration. The key issues for multijunction solar cells are the top and middle solar cell performance and the sub-bandgap transparency. AstroPower has developed a technique to fabricate AlGaAs solar cells on rugged, self-supporting, transparent AlGaAs substrates. Top solar cell efficiencies greater than 11 percent AM0 have been achieved. State-of-the-art GaAs or InP devices will be used for the middle solar cell. GaInAsP will be used to fabricate the bottom solar cell. This material is lattice-matched to InP and offers a wide range of bandgaps for optimization of the three solar cell stack. Liquid phase epitaxy is being used to grow the quaternary material. Initial solar cells have shown open-circuit voltages of 462 mV for a bandgap of 0.92eV. Design rules for the multijunction three solar cell stack are discussed. The progress in the development of the self-supporting AlGaAs top solar cell and the GaInAsP bottom solar cell is presented.

Negley, Gerald H.↗

NASA Langley's Approach to the Sandia's Structural Dynamics Challenge Problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

Horta, Lucas G.↗

Kinematic Modeling of Separation Compression for Paired Approaches to Closely-Spaced Parallel Runways

In a simultaneous paired approach to closely-spaced parallel runways, a pair of aircraft flies in close proximity on parallel approach paths. The longitudinal separation between the aircraft must be maintained within a range that avoids wake encounters and, if one of the aircraft blunders, avoids collision. To increase operational availability, the approach procedure must accommodate a mixture of aircraft sizes and, consequently, approach speeds. In these procedures, the slower aircraft is placed in the lead position. The faster aircraft maintains separation from the slow aircraft in a dependent operation until final approach and flies independently afterward. Due to the higher approach speed of the fast aircraft, longitudinal separation will decrease during final approach. Therefore, the fast aircraft must position itself before the final approach so that it will remain within the safe range of separation as separation decreases. Given the approach geometry and speed schedule for each aircraft, one can use kinematics to estimate the separation loss between a pair of aircraft. A kinematic model can complement fast-time Monte-Carlo simulations of the approach by enabling a tailored reduction in the variation of starting position for the fast aircraft. One could also implement the kinematic model in ground-based or on-board decision support tools to compute the optimal initial separation for a given pair of aircraft. To better match the auto-coupled flight of real aircraft, the paper derives a kinematic model where the speed schedule is flown using equivalent airspeed. The predicted time of flight using the equivalent airspeed kinematic model compares well against a high-fidelity aircraft simulation performing the same approach. This model also demonstrates a modest increase in the predicted loss of separation when contrasted against a kinematic model that assumes the scheduled speed is true airspeed.

Madden, Michael M.↗

Link Budget Analysis of Interrogation of Surface Acoustic Wave Sensors in Metallic Tubular Structures

We report on loss mechanisms contributing to the link budget for interrogation of Surface Acoustic Wave (SAW) devices in metallic tubular structures. Impedance matching losses associated with a SAW device are minimized by design optimization and antenna coupling losses, and resulting propagation losses are measured in metallic tubular structures enabling prediction of interrogation distances with various antenna configurations.

Pingree, Richard↗

Link Budget Analysis of Interrogation of Surface Acoustic Wave Sensors in Metallic Tubular Structures

For presentation at, and publication in the proceedings of, the National Radio Science Meeting, Boulder, CO, January 9-13, 2024.In this paper, we report on loss mechanisms contributing to the link budget for interrogation of Surface Acoustic Wave (SAW) devices in metallic tubular structures. Impedance matching losses associated with a SAW device are minimized by design optimization and antenna coupling losses and resulting propagation losses are measured in metallic tubular structures enabling prediction of interrogation distances with various antenna configurations.

Pingree, Rick↗

Orion Parachute Riser Cutter Development

This paper presents the tests and analytical approach used on the development of a steel riser cutter for the CEV Parachute Assembly System (CPAS) used on the Orion crew module. Figure 1 shows the riser cutter and the steel riser bundle which consists of six individual cables. Due to the highly compressed schedule, initial unavailability of the riser material and the Orion Forward Bay mechanical constraints, JSC primarily relied on a combination of internal ballistics analysis and LS-DYNA simulation for this project. Various one dimensional internal ballistics codes that use standard equation of state and conservation of energy have commonly used in the development of CAD devices for initial first order estimates and as an enhancement to the test program. While these codes are very accurate for propellant performance prediction, they usually lack a fully defined kinematic model for dynamic predictions. A simple piston device can easily and accurately be modeled using an equation of motion. However, the accuracy of analytical models is greatly reduced on more complicated devices with complex external loads, nonlinear trajectories or unique unlocking features. A 3D finite element model of CAD device with all critical features included can vastly improve the analytical ballistic predictions when it is used as a supplement to the ballistic code. During this project, LS-DYNA structural 3D model was used to predict the riser resisting load that was needed for the ballistic code. A Lagrangian model with eroding elements shown in Figure 2 was used for the blade, steel riser and the anvil. The riser material failure strain was fine tuned by matching the dent depth on the anvil with the actual test data. LS-DYNA model was also utilized to optimize the blade tip design for the most efficient cut. In parallel, the propellant type and the amount were determined by using CADPROG internal ballistics code. Initial test results showed a good match with LS-DYNA and CADPROG simulations. Final paper will present a detailed roadmap from initial ballistic modeling and LS-DYNA simulation to the performance testing. Blade shape optimization study will also be presented.

Oguz, Sirri↗

Array-Pattern-Match Compiler for Opportunistic Data Analysis

A computer program has been written to facilitate real-time sifting of scientific data as they are acquired to find data patterns deemed to warrant further analysis. The patterns in question are of a type denoted array patterns, which are specified by nested parenthetical expressions. [One example of an array pattern is ((>3) 0 (not=1)): this pattern matches a vector of at least three elements, the first of which exceeds 3, the second of which is 0, and the third of which does not equal 1.] This program accepts a high-level description of a static array pattern and compiles a highly optimal and compact other program to determine whether any given instance of any data array matches that pattern. The compiler implemented by this program is independent of the target language, so that as new languages are used to write code that processes scientific data, they can easily be adapted to this compiler. This program runs on a variety of different computing platforms. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

James, Mark↗

A critical comparison of CH∙∙∙π versus π∙∙∙π interactions in the benzene dimer: obtaining benchmarks at the CCSD(T) level and assessing the accuracy of lower scaling methods

In this study, we have established CCSD(T)/CBS (Complete Basis Set) limits for 3 stationary points on the benzene dimer potential energy surface, corresponding to the π∙∙∙π (parallel displaced or PD(C 2h ), minimum) and CH∙∙∙π (T-shaped or T(C 2v ), transition state) and tilted T-shaped (or TT(Cs), minimum) bonding scenarios considering both the structure and binding energy. The CCSD(T)/CBS binding energies are -2.65 ± 0.02 (PD), -2.74 ± 0.03 (T), and -2.83 ± 0.01 kcal mol -1 (TT). To this end, the CH∙∙∙π is ~0.2 kcal mol -1 stronger than the π∙∙∙π interaction, whereas the tilting of the CH donating benzene molecule with respect to the other benzene is worth 0.1 kcal mol -1 . As previously discussed in the literature, the MP2 level of theory does not provide a close match for either the energy or structure, yet the SCS-MP2 yields structures in excellent agreement with respect to the CCSD(T) result. It is found that the SCS-MI-MP2 also gives optimized structures very close to SCS-MP2 (within ~0.01 Å of the benchmark). Despite the closer match in structure, the spin-biased MP2 methods (SCS-, SCS-MI-, and SOS-MP2) incorrectly predict the relative stabilities of the isomers. That said, none of the spin biased MP2 methods offers a good compromise between energy and structure for the systems examined. Finally, the CCSD(T)/CBS benchmarks were used to assess the performance of 13 DFT functionals selected from different rungs of Jacob's ladder. Several functionals such as TPSS-D3, B3LYP-D3, B97-D, B97-D3, and B2PLYP-D3 provided a good description of the binding energies for both CH∙∙∙π and π∙∙∙π interactions, yielding values within 6% of the CCSD(T)/CBS benchmark values. Unlike the MP2 methods, these functionals correctly predict the relative stability of the PD(C 2h ) and T(C 2v ) dimers. Further, we find that there is no systematic improvement as Jacob's ladder is ascended (increased complexity of functional). The best functionals that result in a good compromise between structure and energy accuracy are B97-D3 and B2PLYP-D3 for both the CH∙∙∙π and π∙∙∙π interaction. Despite the impressive performance of these functionals, a challenge that remains is ensuring the transferability of these density functionals in accurately describing the interaction between dimers of larger aromatic molecules, the latter requiring high-level benchmarks for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automatic Parameter Tuning for the Morpheus Vehicle Using Particle Swarm Optimization

A high fidelity simulation using a PC based Trick framework has been developed for Johnson Space Center's Morpheus test bed flight vehicle. There is an iterative development loop of refining and testing the hardware, refining the software, comparing the software simulation to hardware performance and adjusting either or both the hardware and the simulation to extract the best performance from the hardware as well as the most realistic representation of the hardware from the software. A Particle Swarm Optimization (PSO) based technique has been developed that increases speed and accuracy of the iterative development cycle. Parameters in software can be automatically tuned to make the simulation match real world subsystem data from test flights. Special considerations for scale, linearity, discontinuities, can be all but ignored with this technique, allowing fast turnaround both for simulation tune up to match hardware changes as well as during the test and validation phase to help identify hardware issues. Software models with insufficient control authority to match hardware test data can be immediately identified and using this technique requires very little to no specialized knowledge of optimization, freeing model developers to concentrate on spacecraft engineering. Integration of the PSO into the Morpheus development cycle will be discussed as well as a case study highlighting the tool's effectiveness.

Birge, B.↗

Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal processing of the photocurrent processes at the outputs of the two detectors is to perform log-matched filtering followed by a summation and peak detection. This implies that neither difference detection, nor Fourier-domain peak detection, which are the staples of the state-of-the-art systems, is optimal when a weak local oscillator is employed.

Erkmen, Baris I.↗

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗

Optimization of the 4-Bed CO2 Scrubber Performance Based on Ground Tests

Testing of ground hardware closely matching the flight design for the 4-Bed CO2Scrubber (4BCO2) has provided a wealth of information about the complex and highly coupled batch process. The 4BCO2 process is a Thermal and Vacuum Swing Adsorption (TVSA) cycle with recirculating flows. The ability to measure CO2concentration at intermediate points in this architecture is new to this ground test system and has revealed a better understanding of system performance and its dependence on system design, operational parameters, and boundary conditions. This paper will discuss a statistical analysis performed to identify significant correlations between performance factors and operational parameters. Using these new insights on the highly coupled system physics, means for improvements to system performance are proposed.

CO2 Removal↗

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

Effect of Illumination Area on the Ultrafast Temporal Response of MSM GaN Photodiodes

We investigate the influence of spatial illumination profiles on the temporal response of metal–semiconductor–metal GaN photodiodes. Using both simulation and experimental measurements, we compare the response curves under two scenarios: illumination confined to the active area between electrodes and extended illumination beyond the contacts. The results show that limiting the beam illumination to the active region significantly sharpens the response, reducing the long decay tails associated with slow carrier drift from peripheral regions. As a result, the experimental data closely match simulation predictions, confirming that illumination geometry plays a critical role in optimizing photodiode performance for ultrafast detection applications.

Carrier drift time↗

Optimizing photonic ring-resonator filters for OH-suppressed near-infrared astronomy

Near-infrared wavelength observations are crucial for understanding numerous fields of astrophysics, such as supernova cosmology and positronium annihilation detection. However, current ground-based observations suffer from an enormous background due to OH emission in the upper atmosphere. One promising way to solve this problem is to use ring-resonator filters to suppress OH emission lines. Here, we discuss our optimization of ring-resonator filter performance from five perspectives: resonance wavelength matching, polarization-independent operation, low insertion loss, low-loss coupling to astronomical instruments, and broadband operation. In the end, we discuss next steps needed for reliable supernova and positronium observations, thus providing a roadmap for future advances in near-infrared astronomy.

42 ENGINEERING↗