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NASA NTRS2014

Growth of CdZnTe Crystals for Radiation Detector Applications by Directional Solidification

Advances in Cadmium Zinc Telluride (Cd(sub 1-x)Zn(sub x)Te) growth techniques are needed for the production of large-scale arrays of gamma and x-ray astronomy. The research objective is to develop crystal growth recipes and techniques to obtain large, high quality CdZnTe single crystal with reduced defects, such as charge trapping, twinning, and tellurium precipitates, which degrade the performance of CdZnTe and, at the same time, to increase the yield of usable material from the CdZnTe ingot. A low gravity material experiment, "Crystal Growth of Ternary Compound Semiconductors in Low Gravity Environment", will be performed in the Material Science Research Rack (MSRR) on International Space Station (ISS). One section of the flight experiment is the melt growth of CdZnTe ternary compounds. This talk will focus on the ground-based studies on the growth of Cd(sub 0.80)Zn(sub 0.20)Te crystals for radiation detector applications by directional solidification. In this investigation, we have improved the properties that are most critical for the detector applications (electrical properties and crystalline quality): a) Electrical resistivity: use high purity starting materials (with reproducible impurity levels) and controlled Cd over pressure during growth to reproducibly balance the impurity levels and Cd vacancy concentration b) Crystalline quality: use ultra-clean growth ampoule (no wetting after growth), optimized thermal profile and ampoule design, as well as a technique for supercool reduction to growth large single crystal with high crystalline quality

Su, Ching-Hua↗

NASA NTRS2016

Computational Study of Flow Interactions in Coaxial Rotors

Although the first idea of coaxial rotors appeared more than 150 years ago, most helicopters have used single main-rotor/tail-rotor combination. Since reactive moments of coaxial rotors are canceled by contra-rotation, no tail rotor is required to counter the torque generated by the main rotor. Unlike the single main rotor design that distributes power to both main and tail rotors, all of the power for coaxial rotors is used for vertical thrust. Thus, no power is wasted for anti-torque or directional control. The saved power helps coaxial rotors reach a higher hover ceiling than single rotor helicopters. Another advantage of coaxial rotors is that the overall rotor diameter can be reduced for a given vehicle gross weight because each rotor provides a maximum contribution to vertical thrust to overcome vehicle weight. However, increased mechanical complexity of the hub has been one of the challenges for manufacturing coaxial rotorcraft. Only the Kamov Design Bureau of Russia had been notably successful in production of coaxial helicopters until Sikorsky built X2, an experimental compound helicopter. Recent developments in unmanned aircraft systems and high-speed rotorcraft have renewed interest in the coaxial configuration. Multi-rotors are frequently used for small electric unmanned rotorcraft partly due to mechanical simplicity. The use of multiple motors provides redundancy as well as cost-efficiency. The multi-rotor concept has rarely been used until recently because of its inherent stability and control problems. However, advances in inexpensive electronic flight control systems have opened the floodgates for small drones using multirotors. Coaxial rotors have started to appear in some multi-rotor configurations. Small coaxial rotors have often been designed using a hundred year old approach that is "sketch, build, fly, and iterate." In that approach, there is no systematic way to explore trade-offs or determine logical next steps. It is neither possible to account for multiple real-world constraints up front in design nor possible to know what performance is possible with a given design. Since unmanned vehicles are sized and optimized for the particular mission, a modern low-fidelity conceptual design and sizing tool that has been used for the design of large helicopters can be used for design of small coaxial rotorcraft. However, unlike most helicopters with single main rotor, the interactions between the upper and lower rotors emerge as an important factor to consider in design because an increase in performance of a multi-rotor system is not proportional to the number of rotors. Interference losses and differences in thrusts between the upper and lower rotors were investigated by theoretical methods as well as a computational fluid dynamics (CFD) method using the Reynolds-Averaged Navier-Stokes (RANS) equations. In this work, hybrid turbulence models are used to investigate the physics of interactions between coaxial rotors and a fuselage that are not well understood. Present study covers not only small-scale drones but also large-scale coaxial rotors for heavy-lifting missions. Considering the recently proposed FAA drone rules that require the flight only in visual line-of-sight, a large multirotor might be used as an airborne carrier for launch and recovery of unmanned aircraft systems with a human operator onboard. For applications to civil operations, their aerodynamic performance and noise levels need to be assessed. Noise is one of the largest limiting factors to rotorcraft operations in urban area. Since the high-frequency noise of multi-rotors may increase the annoyance, noise may turn out to be a key issue that must be addressed for market acceptability. One of the objectives of the present work is to study the effects of inter-rotor spacing and collectives on the performance, efficiency, and acoustics of coaxial rotor systems.

Study↗

NASA NTRS2016

Parallel Adjective High-Order CFD Simulations Characterizing SOFIA Cavity Acoustics

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A temporally fourth-order accurate Runge-Kutta, and spatially fth-order accurate WENO- 5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

CFD↗

NASA NTRS2016

Research Developments in Nondestructive Evaluation and Structural Health Monitoring for the Sustainment of Composite Aerospace Structures at NASA

The use of composite materials continues to increase in the aerospace community due to the potential benefits of reduced weight, increased strength, and manufacturability. Ongoing work at NASA involves the use of the large-scale composite structures for spacecraft (payload shrouds, cryotanks, crew modules, etc). NASA is also working to enable both the use and sustainment of composites in commercial aircraft structures. One key to the sustainment of these large composite structures is the rapid, in-situ characterization of a wide range of potential defects that may occur during the vehicle's life. Additionally, in many applications it is necessary to monitor changes in these materials over their lifetime. Quantitative characterization through Nondestructive Evaluation (NDE) of defects such as reduced bond strength, microcracking, and delamination damage due to impact, are of particular interest. This paper will present an overview of NASA's applications of NDE technologies being developed for the characterization and sustainment of advanced aerospace composites. The approaches presented include investigation of conventional, guided wave, and phase sensitive ultrasonic methods and infrared thermography techniques for NDE. Finally, the use of simulation tools for optimizing and validating these techniques will also be discussed.

Cramer, K. Elliott↗

NASA NTRS2016

Subscale Carbon-Carbon Nozzle Extension Development and Hot Fire Testing in Support of Upper Stage Liquid Rocket Engines

Upper stage and in-space liquid rocket engines are optimized for performance through the use of high area ratio nozzles to fully expand combustion gases to low exit pressures increasing exhaust velocities. Due to the large size of such nozzles and the related engine performance requirements, carbon-carbon (C/C) composite nozzle extensions are being considered for use in order to reduce weight impacts. NASA and industry partner Carbon-Carbon Advanced Technologies (C-CAT) are working towards advancing the technology readiness level of large-scale, domestically-fabricated, C/C nozzle extensions. These C/C extensions have the ability to reduce the overall costs of extensions relative to heritage metallic and composite extensions and to decrease weight by 50%. Material process and coating developments have advanced over the last several years, but hot fire testing to fully evaluate C/C nozzle extensions in relevant environments has been very limited. NASA and C-CAT have designed, fabricated and hot fire tested multiple subscale nozzle extension test articles of various C/C material systems, with the goal of assessing and advancing the manufacturability of these domestically producible materials as well as characterizing their performance when subjected to the typical environments found in a variety of liquid rocket and scramjet engines. Testing at the MSFC Test Stand 115 evaluated heritage and state-of-the-art C/C materials and coatings, demonstrating the capabilities of the high temperature materials and their fabrication methods. This paper discusses the design and fabrication of the 1.2k-lbf sized carbon-carbon nozzle extensions, provides an overview of the test campaign, presents results of the hot fire testing, and discusses potential follow-on development work.

Gradl, Paul↗

NASA NTRS2016

Temporal Gain Correction for X-Ray Calorimeter Spectrometers

Calorimetric X-ray detectors are very sensitive to their environment. The boundary conditions can have a profound effect on the gain including heat sink temperature, the local radiation temperature, bias, and the temperature of the readout electronics. Any variation in the boundary conditions can cause temporal variations in the gain of the detector and compromise both the energy scale and the resolving power of the spectrometer. Most production X-ray calorimeter spectrometers, both on the ground and in space, have some means of tracking the gain as a function of time, often using a calibration spectral line. For small gain changes, a linear stretch correction is often sufficient. However, the detectors are intrinsically non-linear and often the event analysis, i.e., shaping, optimal filters etc., add additional non-linearity. Thus for large gain variations or when the best possible precision is required, a linear stretch correction is not sufficient. Here, we discuss a new correction technique based on non-linear interpolation of the energy-scale functions. Using Astro-HSXS calibration data, we demonstrate that the correction can recover the X-ray energy to better than 1 part in 104 over the entire spectral band to above 12 keV even for large-scale gain variations. This method will be used to correct any temporal drift of the on-orbit per-pixel gain using on-board calibration sources for the SXS instrument on the Astro-H observatory.

X-ray detector X-ray spectrometer X-ray calorimete↗

NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗

NASA NTRS2015

Parallel Adaptive High-Order CFD Simulations Characterizing SOFIA Cavitiy Acoustics

This paper presents large-scale MPI-parallel computational uid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft fuselage of a Boeing 747SP. These simulations focus on how the unsteady ow eld inside and over the cavity interferes with the optical path and mounting structure of the telescope. A tempo- rally fourth-order accurate Runge-Kutta, and a spatially fth-order accurate WENO-5Z scheme were used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh re nement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32k CPU cores and 4 billion compu- tational cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregular numerical cost associated with blocks con- taining boundaries. Limits to scaling beyond 32k cores are identi ed, and targeted code optimizations are discussed.

Parallell↗

NASA NTRS2019

Development of Large-Scale Magnetic Calorimeter Arrays

We describe performance of large-scale arrays of metallic magnetic calorimeters (MMCs) we are developing to meet requirements of the Lynx X-ray Microcalorimeter (LXM) instrument in the astrophysics mission concept Lynx. We have fabricated prototypes with 55,800 x-ray pixels thermally connected to 5,688 MMC sensors. Subarrays demonstrate three types of pixels, which have different energy and spatial resolution goals in LXM. Pixel pitch is 50 or 25 µm. For two subarrays, use of position sensitive detectors, in a "hydra" configuration with 25 x-ray absorbers per sensor, helps achieve a large focal plane by increasing pixel count relative to readout channels. Since each absorber has a different thermal link to its sensor, it generates a different pulse shape and enables discrimination of pixel position. Superconducting wiring from all sensors was brought out to the perimeter of the overall array using multiple buried metal layers planarized by Chemical Mechanical Planarization to achieve high critical current, low inductance, and high fabrication yield. An automated, algorithmic approach was used to layout the complex wiring pattern. For readout with existing small arrays of Superconducting Quantum Interference (SQUID) amplifiers, 112 selected pixels were connected to wire bond pads. In hydras, we successfully identified 25 pulse shapes using rise-time and pulse height. Pulse shapes were similar to simulations. We measured noise and responsivity to substrate temperature and applied x-ray pulses. While we designed sensors to have high inductance to relative to stray inductance of wiring, we had only mismatched (lower input inductance) SQUIDs available in our current apparatus, giving non-optimized resolution. We compared measured and calculated energy resolutions. We have the required sensitivity to reach < 3 eV FWHM resolution for 6 keV x-rays, required for the LXM Main Array, and the ability to discriminate the 25 different absorber pixels down to energies < 300 eV.

microcalorimeters↗

NASA NTRS2019

Tracking Aerosol Convective Interactions Experiment (TRACER) Science Plan

Convective clouds play an important role in the Earth's climate system as a driver of large-scale circulations and a primary mechanism for the transport of heat, moisture, aerosols, and momentum throughout the troposphere. Despite their climatic importance, multi-scale models continue to have persistent biases produced by insufficient representation of convective clouds. This is the result of an incomplete understanding of key processes such as convective initiation, updraft and downdraft dynamics, cloud and precipitation microphysics, and aerosol-convection interactions.The Aerosol-Cloud-Precipitation-Climate Initiative, an international research group dedicated to advancing understanding of aerosol impacts on clouds relevant to climate, has identified the Houston, Texas region as an optimal location for targeted studies of aerosol-convection interactions within frequently developing isolated deep convection. Houston lies within a humid subtropical climate regime, where onshore flow and sea-breeze convection interact with a range of aerosol conditions associated with Houston's urban and industrial emissions. Pilot studies have suggested that convective clouds in this region are potentially significantly impacted by the varying aerosol conditions.

Jensen, M.↗

NASA NTRSDate not supplied

Hot-Fire Testing Results of Additively Manufactured NASA HR-1 towards Large Scale Implementation of Channel Wall Nozzles

Additive manufacturing (AM) has provided new design and manufacturing opportunities to reduce cost and schedules, consolidate parts, and optimize performance. One technique being evaluated is Laser Powder Directed Energy Deposition (LP-DED), which provides a significant increase in scale compared to Laser Powder Bed Fusion (L-PBF). NASA along with industry partners have been developing the LP-DED process to demonstrate internal channel geometry and development components for use in liquid rocket engine channel cooled nozzles. One material that has been the focus of this development is NASA HR-1, an Iron-Nickel based superalloy optimized for use in high pressure hydrogen environments. Material properties and process characterization has been completed on the high density thin-wall material in addition to advancements of the supply chain. NASA has also completed fabrication of several subscale and full scale channel wall nozzles in LP-DED NASA HR-1 and completed hot-fire testing. This includes refinement of the process to produce thin-walls and various channel geometries to meet the requirements for channel wall nozzle applications. This paper will provide an overview of the LP-DED process development, material characterization and properties, component manufacturing, and hot-fire testing. Hot-fire testing was completed for a lander-class 7K-lbf thrust chamber using Liquid Oxygen (LOX)/Methane. The design overview and results from hot-fire testing will be presented in addition to hardware development for future testing on 2K-lbf and 35k-lbf thrust chambers and large-scale manufacturing technology demonstrators.

Paul Gradl↗

NASA NTRS2021

Improved Estimates of Pentad Precipitation through the Merging of Independent Precipitation Datasets

Three independent, quasi-global, gridded datasets of precipitation (a rain gauge-based dataset, the satellite-only component of the NASA Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission [IMERG] Final Run precipitation product, and precipitation estimates derived from NASA Soil Moisture Active Passive [SMAP] soil moisture retrievals), are objectively combined into a single pentad precipitation dataset at 36-km resolution using a unique approach based on extended triple collocation. The quality of each of the four datasets is then evaluated against independent observations. When a global land surface model at 36-km resolution is integrated four times, once utilizing the merged precipitation forcing and once with each of the three contributing datasets, the near-surface soil moisture variations produced with the merged forcing validate best against independent satellite-based soil moisture fields. In addition, the merged dataset is found to be more consistent, relative to each contributor, with estimates of air temperature variations across the globe. The merged dataset thus appears to draw successfully on the complementary strengths of each contributor: the particularly high quality of the rain gauge-based dataset in areas of high gauge density, the more uniform accuracy across the globe of the IMERG data, and the moderate accuracy, particularly in semi-arid regions, of the soil moisture retrieval-based data. Plain Language Summary Obtaining measurements of precipitation across the globe can be challenging. Rain gauges in some ways provide the most accurate measurements, but gauges are absent in many parts of the world, and even where they exist, they only measure precipitation at the gauge itself and therefore may not provide an accurate large-scale average. Satellite-based estimates of precipitation largely overcome these problems, but such data have their own issues, notably a “snapshot” (rather than a time-average) character of the measurements and difficulty associated with interpreting the measured radiances in the presence of complex land surfaces. In the present paper, we use a novel approach to generate a “merged” dataset, one that optimally combines the gauge precipitation information and the satellite-based precipitation information with a third set of estimates derived from soil moisture retrievals. The merged precipitation dataset and each of the three contributors (aggregated here to 5-day averages at a spatial resolution of about 36-km) are then evaluated for consistency with independent geophysical fields. The merged dataset is found to perform best, a clear indication that it takes proper advantage of the complementary strengths of each contributor and, accordingly, that the presented approach for merging the different contributors is indeed viable.

Precipitation↗

NASA NTRSDate not supplied

Process Development and Hot-fire Testing of Additively Manufactured NASA HR-1 for Liquid Rocket Engine Applications

Additive manufacturing (AM) has provided new design and manufacturing opportunities to reduce cost and schedules, consolidate parts, and optimize performance. One technique being evaluated is Laser Powder Directed Energy Deposition (LP-DED), which provides a significant increase in scale compared to Laser Powder Bed Fusion (L-PBF). NASA along with industry partners have been developing the LP-DED process to demonstrate internal channel geometry and development components for use in liquid rocket engine channel cooled nozzles. Optimized materials in the extreme high pressure and hydrogen environment for liquid rocket engines remains a key challenge. NASA has advanced an enabling material called NASA HR-1 (Hydrogen Resistant -1) as a solution using AM techniques. NASA HR-1 is a high-strength Fe-Ni superalloy designed to resist high pressure, hydrogen environment embrittlement, oxidation, and corrosion. NASA HR-1 meets materials requirements for liquid rocket engine components, including good hydrogen resistance, high conductivity, good low cycle fatigue performance, and high elongation and strength for components in high heat flux environments. Material properties and process characterization have been completed on the high density thin-wall material in addition to advancements of the supply chain. NASA has also completed fabrication of several subscale and full-scale channel wall nozzles in LP-DED NASA HR-1 and completed hot-fire testing. This includes refinement of the process to produce thin-walls and various channel geometries to meet the requirements for channel wall nozzle applications. This paper will provide an overview of the LP-DED process development, material characterization and properties, component manufacturing, and hot-fire testing. Hot-fire testing was completed for a lander-class 7K-lbf thrust chamber using Liquid Oxygen (LOX)/Methane. The design overview and results from hot-fire testing will be presented in addition to hardware development for future testing on 2K-lbf and 35k-lbf thrust chambers and large-scale manufacturing technology demonstrators.

DED↗

NASA NTRSDate not supplied

Process Development and Hot-fire Testing of Additively Manufactured NASA HR-1 for Liquid Rocket Engine Applications

Additive manufacturing (AM) has provided new design and manufacturing opportunities to reduce cost and schedules, consolidate parts, and optimize performance. One technique being evaluated is Laser Powder Directed Energy Deposition (LP-DED), which provides a significant increase in scale compared to Laser Powder Bed Fusion (L-PBF). NASA along with industry partners have been developing the LP-DED process to demonstrate internal channel geometry and development components for use in liquid rocket engine channel cooled nozzles. Optimized materials in the extreme high pressure and hydrogen environment for liquid rocket engines remains a key challenge. NASA has advanced an enabling material called NASA HR-1 (Hydrogen Resistant -1) as a solution using AM techniques. NASA HR-1 is a high-strength Fe-Ni superalloy designed to resist high pressure, hydrogen environment embrittlement, oxidation, and corrosion. NASA HR-1 meets materials requirements for liquid rocket engine components, including good hydrogen resistance, high conductivity, good low cycle fatigue performance, and high elongation and strength for components in high heat flux environments. Material properties and process characterization have been completed on the high density thin-wall material in addition to advancements of the supply chain. NASA has also completed fabrication of several subscale and full-scale channel wall nozzles in LP-DED NASA HR-1 and completed hot-fire testing. This includes refinement of the process to produce thin-walls and various channel geometries to meet the requirements for channel wall nozzle applications. This paper will provide an overview of the LP-DED process development, material characterization and properties, component manufacturing, and hot-fire testing. Hot-fire testing was completed for a lander-class 7K-lbf thrust chamber using Liquid Oxygen (LOX)/Methane. The design overview and results from hot-fire testing will be presented in addition to hardware development for future testing on 2K-lbf and 35k-lbf thrust chambers and large-scale manufacturing technology demonstrators.

Additive Manufacturing↗

NASA NTRS2014

Controllable Multi-Functional Heat Exchanger for Space Applications

Team Spacering will design SpaceRing, a cooling and waste heat recycling system that addresses NASA’s interest for a cooling and power-generating unit in its prototype deep space habitat[1]. The merits of this system are as follows: - Controllable cooling is critical in maintaining a habitable environment and in the functionality of life support systems, powering electronics and other devices in a spacecraft. - Power is expensive to produce in a space environment. Converting wasted thermal energy into electricity will save energy and money for the space station. Space habitation is a highly complex endeavor. Consequently, the SpaceRing must adhere to additional constraints, which include: - Lack of natural fluid or gas convection due to micro-gravity environment - Limited range for heat source and cold sink temperature - Subject to high fluctuations of incoming thermal energy - Minimal weight due to the high cost of transporting items into space After consulting with NASA and experts in thermal studies, several design objectives were identified and are listed below in order of importance: - High cooling capacity - Reliable safety control and alert system - Maximization of energy generation from wasted heat - Optimization of cooling capability and power generation - Long operational life and minimization of maintenance In space, conventional cooling systems utilize passive heat pipe systems for small-scale heat rejection and pumped pipes with heat exchangers for large-scale heat rejection. Thermal power generation in space is mainly achieved by using thermoelectric material that produces electric energy from temperature differentials. We propose a design that combines cooling and thermoelectric power generation. Using a hot pipe connected to a heat source, a cold pipe connected to a radiator, a heat exchanger in contact with both pipes, and a pump in each pipe to move the fluid, we make an active cooling system. The thermoelectric material is inserted in the heat exchanger between the hot and cold pipes to extract energy from the maximum temperature difference coming from the two pipes. It also provides controllable cooling capacity through the use of the thermoelectric material as cooling modules. We have tested our system under target heat source and sink conditions and measured the temperatures and flow rates. Our preliminary results are promising, demonstrating the output of 25 Watts of power on average. We are in the process of running control tests to compare the heat transfer performance without the thermoelectric generators, which is vital in determining whether or not the generators introduce an unacceptable amount of thermal resistance. While some control tests have been run already, the results have been noisy. We have modified our testing environment and data acquisition methods to allow for simple comparison between the control test results and thermoelectric performance results. Lastly, we have modified the heat exchanger design slightly to include acrylic baffles. This will allow the heat to flow through the heat exchanger more efficiently. We have presented our preliminary results to NASA and will deliver the final product by the end of May 2014.

Lee Xiong↗

DOE OSTI2024

QFw: A Quantum Framework for Large-scale HPC Ecosystems

This work extends Quantum Framework (QFw) by integrating it with Northwest Quantum Simulator (NWQ-Sim) and by introducing a lightweight python library that allows multiple frontends (e.g., Qiskit) to interact with QFw. This extension enables QFw to flexibly decouple frontends from backends (e.g., NWQ-Sim). We demonstrate this capability by executing a Greenberger-Horne-Zeilinger (GHZ) circuit using Qiskit and Pennylane with NWQ-Sim and Tensor-Network Quantum Virtual-Machine (TN-QVM). QFw enables easy scaling to multiple nodes. We showcase this with scaling tests using GHZ with up to 32 qubits for different number of nodes on the Frontier supercomputer. And, to demonstrate the use of QFw for real world problems, we solve a metamaterial optimization problem, using a Quantum Approximate Optimization Algorithm (QAOA). We observe that QFw over NWQ-Sim marginally improves Qiskit-aer’s accuracy in reaching the lowest energy state. These additions to QFw prepare it to run hybrid applications in a hybrid resource environment since it treats actual quantum hardware and simulators alike.

Chundury, Srikar↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

There and Back Again: Reimagining Cryogenic Cooling for Scalable Arrays of Dilution Refrigerators for future Quantum Datacenters

While pulse tube cryocoolers enabled the rapid expansion of dilution refrigerator technology over the past two decades, the transition to large-scale quantum systems is now driving a reassessment of the DR’s higher-temperature-stage cooling strategies and how these systems can be effectively scaled in a modular way. Quasi-wet architectures based on centralized cryoplants and forced-flow helium distribution offer compelling advantages in energy efficiency, operational cost, and scalability. With appropriate redundancy, standardized interfaces, and optimized distribution system designs, these architectures will provide a practical and robust path forward for the next generation of quantum computing infrastructure.

Hansen, B. [Fermilab]↗