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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 1,027 records · Page 57

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗

Research and technology

Activities of the Goddard Space Flight Center are described in the areas of planets and interplanetary media, comets, astronomy and high-energy physics, solar physics, atmospheres, terrestrial physics, ocean science, sensors and space technology, techniques, user space data systems, space communications and navigation, and system and software engineering. Flight projects and mission definition studies are presented, and institutional technology is described.

Source record↗

Hybrid Reality Lab Capabilities - Video 2

Our Hybrid Reality and Advanced Operations Lab is developing incredibly realistic and immersive systems that could be used to provide training, support engineering analysis, and augment data collection for various human performance metrics at NASA. To get a better understanding of what Hybrid Reality is, let's go through the two most commonly known types of immersive realities: Virtual Reality, and Augmented Reality. Virtual Reality creates immersive scenes that are completely made up of digital information. This technology has been used to train astronauts at NASA, used during teleoperation of remote assets (arms, rovers, robots, etc.) and other activities. One challenge with Virtual Reality is that if you are using it for real time-applications (like landing an airplane) then the information used to create the virtual scenes can be old (i.e. visualized long after physical objects moved in the scene) and not accurate enough to land the airplane safely. This is where Augmented Reality comes in. Augmented Reality takes real-time environment information (from a camera, or see through window, and places digitally created information into the scene so that it matches with the video/glass information). Augmented Reality enhances real environment information collected with a live sensor or viewport (e.g. camera, window, etc.) with the information-rich visualization provided by Virtual Reality. Hybrid Reality takes Augmented Reality even further, by creating a higher level of immersion where interactivity can take place. Hybrid Reality takes Virtual Reality objects and a trackable, physical representation of those objects, places them in the same coordinate system, and allows people to interact with both objects' representations (virtual and physical) simultaneously. After a short period of adjustment, the individuals begin to interact with all the objects in the scene as if they were real-life objects. The ability to physically touch and interact with digitally created objects that have the same shape, size, location to their physical object counterpart in virtual reality environment can be a game changer when it comes to training, planning, engineering analysis, science, entertainment, etc. Our Project is developing such capabilities for various types of environments. The video outlined with this abstract is a representation of an ISS Hybrid Reality experience. In the video you can see various Hybrid Reality elements that provide immersion beyond just standard Virtual Reality or Augmented Reality.

Delgado, Francisco J.↗

A view on the current and future impact of research reactors

Full text of publication follows. The current fleet of nuclear research reactors worldwide is nearly 70 years old. These reactors have proven to be extremely valuable tools of nuclear science and engineering with a broad and interdisciplinary impact. To date, research reactors are utilized as tools for understanding the physics, operations, and safety of nuclear fission systems. In addition, they are used as intense sources of radiation in support of irradiation testing and nondestructive examination of materials. As this fleet of reactors ages, an urgent need exists to establish new facilities that can propel the benefit of these reactors into the 21. century. In fact, an opportunity exists to build research reactors based on technology concepts that are being considered for nuclear energy reactors. This may include high temperature gas cooled and/or molten salt based advanced and micro reactor concepts. Such future reactors should be designed to maintain the broad utility of current reactors in research and education. However, modern research reactors can be purposefully designed and instrumented to access neutronic and thermal hydraulic information that would support the development and validation of reactor multi-physics modeling and simulation techniques. In this case, the entire phenomenological paradigm of the reactor may be captured to understand the neutronic multiscale and its impact on operations and safety. Moreover, the generated data can be channeled to drive anticipatory examination of the state of the reactor. In general, a symbiotic relation may be envisioned between the modern research reactor and power reactor fleets, which could facilitate the safe and efficient implementation of clean nuclear energy. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

New Rover Conops with High-Performance Onboard Computing: Give Up Raw Data to Reduce Ops Cost and Do More Science

A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.

Didier, A.↗

Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems

This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances. Our extension is inspired by the concept of parameterized ordinary differential equations, which are widely investigated in computational science and engineering contexts, where characteristics of the governing equations vary over the input parameters. We apply the proposed parameterized NODEs (PNODEs) for learning latent dynamics of complex dynamical processes that arise in computational physics, which is an essential component for enabling rapid numerical simulations for time-critical physics applications. For this, we propose an encoder-decoder-type framework, which models latent dynamics as PNODEs. We demonstrate the effectiveness of PNODEs with important benchmark problems from computational physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗

A First Principles Approach to Spectral Phonon Transport in Heterostructures

Understanding thermal transport across interfaces which give rise to a thermal resistance (also known as Kapitza resistance) is a critical issue affecting the development of nanotechnologies. Much modern and emergent nanotechnology consist of adjacent materials, and phonon mediated heat transfer governs thermal behavior across internal interfaces in these devices. The physics of thermal transport in solids are governed both by phenomena occurring at the atomic scale and interactions with the material's microstructure. The forecasting of fundamental quantities such as temperature, heat flux and thermal conductivity typically employs the semi-classical Boltzmann transport equation to predict the macroscopic behavior of materials in terms of the microscopic dynamics of its heat carriers. Kapitza resistance was first discovered in liquid helium experiments and has led to a fundamental research thrust in micro and nano-scale heat transport, the behavior of thermal carriers across internal interfaces. Thermal interfacial resistance (TIR) is a widely studied phenomenon, first engaged by Swartz and Pohl through their development of the acoustic and diffuse mismatch methods, then continued through myriad efforts with varying methods and approaches in an attempt to resolve carrier behavior at thermal interfaces. Many of the fundamental approaches to TIR have been at the nanoscale, and research is conducted with molecular dynamics (MD) and density functional theory (DFT) methods. The limitations of these methods is system size; atomistic methods tend to be limited to system sizes of 100,000 atoms or less. Larger length-scale methods have also been pursued, based on the principles of acoustic or diffuse mismatch, but not all include simulation of TIR using a full phonon band spectrum, or temperature dependent methods. Our approach to enabling phonon transport in layered materials draws upon our previous work of demonstrating spectrally coupled phonon transport in homogeneous and heterogeneous materials. We use a semi-analytical approach in which the Bose-Einstein (B-E) statistics set the strength of the phonon radiance in a frequency group, but the B-E statistics are informed with information from the transport system. The B-E statistics in a single frequency group feels the influence of all the groups through the spatial temperature. We also include a new field term which is an indicator of the amount of non-equilibrium behavior of the phonon spectrum---this is added to the phonon source term in all groups to ensure closure and conservation of energy, as the phonon groups in the transport system and the analytical systems are coupled. This work builds upon our previous approach by adding a phonon coupling term at an internal interface, using the principles of the DMM through transmission and reflection coefficients. In this work, the coefficients are determined through computing a common temperature at the interface, influenced by the phonon band structure of both materials, in effect, providing mixing between the two material systems and using the common temperature to set the strength of the phonon radiance at the boundaries on either side of the interface. Our approach uses material properties computed along various crystallographic orientations, and while some isotropy is built into the interface condition, the material properties weight the phonon distributions in the proper crystalline direction. Greater resolution of phonon behavior in proximity to an interface, and more accurate predictions of TIR are obtained. While it is true the assumption of diffuse mismatch can yield inconsistent results compared to experiment especially at low temperatures, this work focuses on room temperature and beyond effects, for future applications in nuclear fuel, or thermoelectric devices; a modified mismatch approach may be feasible if applied properly. Additionally, our methods focus on bridging mesoscale to engineering scale

36 MATERIALS SCIENCE↗

Total and Spectral Solar Irradiance Sensor (TSIS) Project Overview

The main objective of the Total and Spectral solar Irradiance Sensor (TSIS) is to acquire measurements to determine the direct and indirect effects of solar radiation on climate. TSIS total solar irradiance measurements will extend a 37-year long uninterrupted measurement record of incoming solar radiation, the dominant energy source driving the Earths climate and the most precise indicator of changes in the Suns energy output. TSIS solar spectral irradiance measurements will determine the regions of the Earths multi-layered atmosphere that are affected by solar variability, from which the solar forcing mechanisms causing changes in climate can be quantified. TSIS includes two instruments: the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM), integrated into a single payload. The TSIS TIM and SIM instruments are upgraded versions of the two instruments that are flying on the Solar Radiation and Climate Experiment (SORCE) mission launched in January 2003. TSIS was originally planned for the nadir-pointing National Polar-orbiting Operational Environmental Satellite System (NPOESS) spacecraft. The TSIS instrument passed a Critical Design Review (CDR) for NPOESS in December 2009. In 2010, TSIS was re-planned for the Joint Polar Satellite System (JPSS) Polar Free Flyer (PFF). The TSIS TIM, SIM, and associated electronics were built, tested, and successfully completed pre-ship review as of December 2013.In early 2014, NOAA and NASA agreed to fly TSIS on the International Space Station (ISS). In the FY16 Presidents Budget, NASA assumes responsibility for the TSIS mission on ISS. The TSIS project includes requirements, interface, design, build and test of the TSIS payload, including an updated pointing system, for accommodation on the ISS. It takes advantage of the prior development of the TSIS sensors and electronics. The International Space Station (ISS) program contributions include launch services and robotic installation of the TSIS payload onto an ISS Express Logistics Carrier, mission operations, and communications. Total and Spectral solar irradiance data products will be produced, calibrated, and made publically available through the Goddard Earth Science Data and Information Services Center (GES DISC).The NASA GSFC TSIS project at GSFC is responsible for project management, system engineering, safety and mission assurance, and engineering oversight for the TSIS payload. The TSIS project has contracted with the University of Colorado Laboratory for Atmospheric and Space Physics (LASP) for the design, development and testing of TSIS, support for ISS integration, science operations of the TSIS instrument, data processing, data evaluation and delivery to the GES DISC. TSIS will be delivered to Kennedy Space Center for integration in 2017, with launch and installation onto ISS planned for late 2017-early 2018. After a 90-day check-out period, NASA plans five years of TSIS operations.

spectral emission↗

SPACE: 3D parallel solvers for Vlasov-Maxwell and Vlasov-Poisson equations for relativistic plasmas with atomic transformations

A parallel, relativistic, three-dimensional particle-in-cell code SPACE has been developed for the simulation of electromagnetic fields, relativistic particle beams, and plasmas. In addition to the standard second-order Particle-in-Cell (PIC) algorithm, SPACE includes efficient novel algorithms to resolve atomic physics processes such as multi-level ionization of plasma atoms, recombination, and electron attachment to dopants in dense neutral gases. SPACE also contains a highly adaptive particle-based method, called Adaptive Particle-in-Cloud (AP-Cloud), for solving the Vlasov-Poisson problems. It eliminates the traditional Cartesian mesh of PIC and replaces it with an adaptive octree data structure. The code's algorithms, structure, capabilities, parallelization strategy, and performance have been discussed. Additionally, typical examples of SPACE applications to accelerator science and engineering problems are described.

43 PARTICLE ACCELERATORS↗

Engineering a new-to-nature cascade for phosphate-dependent formate to formaldehyde conversion in vitro and in vivo

Formate can be envisioned at the core of a carbon-neutral bioeconomy, where it is produced from CO 2 by (electro-)chemical means and converted into value-added products by enzymatic cascades or engineered microbes. A key step in expanding synthetic formate assimilation is its thermodynamically challenging reduction to formaldehyde. Here, we develop a two-enzyme route in which formate is activated to formyl phosphate and subsequently reduced to formaldehyde. Exploiting the promiscuity of acetate kinase and N-acetyl-γ-glutamyl phosphate reductase, we demonstrate this phosphate (P i )-based route in vitro and in vivo. We further engineer a formyl phosphate reductase variant with improved formyl phosphate conversion in vivo by suppressing cross-talk with native metabolism and interface the P i route with a recently developed formaldehyde assimilation pathway to enable C2 compound formation from formate as the sole carbon source in Escherichia coli. The P i route therefore offers a potent tool in expanding the landscape of synthetic formate assimilation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stabilization of high-performance rock-salt LiMnSbTe3 thermoelectrics with embedded van der Waals-like gaps

Rock-salt-structured compounds like lead chalcogenides are promising thermoelectrics, as their high symmetry, strong anharmonicity, and favorable phase behavior collectively lead to high performance by enabling large power factors and ultralow thermal conductivity. Here, we report LiMnSbTe 3 , a new rock-salt semiconductor stabilized through targeted chemical design by combining hexagonal MnTe with cubic LiSbTe 2 . Embedded in the highsymmetry matrix, van der Waals-like gaps form due to Sb 2 Te 3 nanoscale segregation, which acts as effective phonon-scattering centers, leading to a low lattice thermal conductivity of 0.37Wm- 1 K -1 at 873 K with alloy scattering from disordered cations. The ordered local structure of Sb2Te 3 -type vdW-like gaps and the cross-gap interaction facilitate the carrier transport. Aided by energyconverged valence bands and a paramagnon drag effect, high Seebeck coefficients and enhanced power factor can be achieved, leading to a high ZT of 1.2 at 873 K. Furthermore, introducing Mn deficiency increases ZT to 1.5, highlighting the potential for higher performance through optimized doping or alloying. A segmented single-leg thermoelectric module achieves an output power density of 0.52 Wcm -2 and an efficiency of 8.7% under ΔT of 478 K, further demonstrating its promising thermoelectric applications.

42 ENGINEERING↗

Thermodynamics and transport in molten chloride salts and their mixtures

Relationship between thermophysical properties and phonon mean free path. Heat capacity, viscosity, and thermal conductivity in ionic liquids decrease as mean free path decreases and dynamics become less “solid-like” and collect motion diminishes.

Cockrell, C. [Nuclear Futures Institute, Bangor Un↗

3D‐Printed Structure Boosts the Kinetics and Intrinsic Capacitance of Pseudocapacitive Graphene Aerogels

Abstract The performance of pseudocapacitive electrodes at fast charging rates are typically limited by the slow kinetics of Faradaic reactions and sluggish ion diffusion in the bulk structure. This is particularly problematic for thick electrodes and electrodes highly loaded with active materials. Here, a surface‐functionalized 3D‐printed graphene aerogel (SF‐3D GA) is presented that achieves not only a benchmark areal capacitance of 2195 mF cm −2 at a high current density of 100 mA cm −2 but also an ultrahigh intrinsic capacitance of 309.1 µF cm −2 even at a high mass loading of 12.8 mg cm −2 . Importantly, the kinetic analysis reveals that the capacitance of SF‐3D GA electrode is primarily (93.3%) contributed from fast kinetic processes. This is because the 3D‐printed electrode has an open structure that ensures excellent coverage of functional groups on carbon surface and facilitates the ion accessibility of these surface functional groups even at high current densities and large mass loading/electrode thickness. An asymmetric device assembled with SF‐3D GA as anode and 3D‐printed GA decorated with MnO 2 as cathode achieves a remarkable energy density of 0.65 mWh cm −2 at an ultrahigh power density of 164.5 mW cm −2 , outperforming carbon‐based supercapacitors operated at the same power density.

asymmetric supercapacitors↗

MALDI-MS screening of microbial colonies with isomer resolution to select fatty acid desaturase variants

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid MS assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Lastly, we used the fabA deficient chassis to concomitantly express a non-native acyl- ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Facile All-Optical Method for In Situ Detection of Low Amounts of Ammonia

As a key precursor for nitrogenous compounds and fertilizer, ammonia affects our lives in numerous ways. Rapid and sensitive detection of ammonia is essential, both in environmental monitoring and in process control for industrial production. Here we report a novel and nonperturbative method that allows rapid detection of ammonia at low concentrations, based on the all-optical detection of surface-enhanced Raman signals. We show that this simple and affordable approach enables ammonia probing at selected regions of interest with high spatial resolution, making in situ and operando observations possible.

09 BIOMASS FUELS↗

A novel energy balance approach for a verifiable and accurate solution of radiation extinction in purely absorbing particle clouds

Here we consider the problem of radiation transport through purely absorbing particle clouds. The gold-standard solution of particle-resolved Monte Carlo ray-tracing method to this problem is computationally expensive and therefore solving the radiation transport equation (specifically, the Beer-Bouguer law (BB-law)) on a Eulerian mesh is often preferred. While the absorption coefficient in the real problem is infinite, the BB-law approximates it to be a finite number in the form of number density through a set of assumptions. For particle clouds that do not obey these assumptions, the BB-law predicts an incorrect exponential decay. Also, when the number density is computed using the nearest-neighbor approach, the BB-law solution diverges when the Eulerian mesh size becomes closer to or smaller than the particle size. This numerical divergence is due to the homogenization error. Although the filtering strategy for number density minimizes the homogenization error, it still converges to an incorrect exponential decay for particle clouds that break the BB-law constraints and the cost of the filtering is equivalent to that of the gold-standard solution. In this study, we develop a novel, highly accurate, verifiable and cost-effective solution to the radiation transport equation on a Eulerian domain using an energy balance approach where we derive an expression for the absorption coefficient as a function of particle and Eulerian mesh sizes. We apply our new method to Poisson and turbulent particle clouds that violate all the BB-law constraints and show that the solution is converging upon the mesh refinement, and eventually, we recover the same gold-standard solution for a much cheaper computational cost.

42 ENGINEERING↗