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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 217 records · Page 12

Development of a self-lubricating high-efficiency hybrid seal composed of carbon nanotube-coated metal meshes for CSP turbomachinery (SETO CPS #36333 Final Report)

In turbomachinery, internal leakage flow accounts for up to 3% of the total thermodynamic cycle energy loss. Tradeoff must be made between the sealing efficiency (smaller clearance) and the friction and wear issues for interfering with the shaft (larger clearance). This ORNL-Danfoss joint effort developed a novel hybrid seal composed of carbon nanotube (CNT)-coated metal meshes. The CNT growth process was based on a self-catalyzing chemical vapor deposition and these multiwall CNTs were well aligned with high crystallinity. This hybrid material structure takes advantage of the CNT’s low-friction nature and uses the metal mesh as an extendable backbone. Full-scale experimental seals were designed, fabricated, and optimized for sealing performance and durability. The CNT-coated metal mesh seal demonstrated superior gas sealing efficiency to the baseline labyrinth seal and significantly improved shaft surface protection compared with the state-of-the-art superalloy brush seal on the static rig and full-scale compressor dynamometer tests. The CNT-metal mesh seal is low-cost and scalable and can potentially benefit wide applications, including CSP and other power generation, marine, automotive, and HVAC.

36 MATERIALS SCIENCE↗

Advances on CHP District Energy and Microgrids Deployment: Simplified Tool for Rapidly Deploying Feasibility Analytics for the Non-Technical User (Final Technical Report)

Community energy systems have proven to have the potential to improve cost efficiency, resilience, and decarbonize. However, investing in community energy systems such as community microgrids or district energy systems is a complex decision due to the high initial investment and the uncertainties associated with the long development time and lifecycle of the project. Tools that make feasibility assessments accessible to non-technical users like investors, policymakers, and other stakeholders will result in more feasibility analyses completed, more candidate projects identified, and more community energy systems deployed. The pilot tool developed under this award is named Energy Fellow. Energy Fellow allows technical and non-technical users to complete feasibility analyses for district energy systems and community microgrids. This is the first software tool of its kind designed for non-technical users and available at no cost. Its scope was adjusted to a 25x25-mile region within the Houston area in Texas to make its development compatible with the funding available. However, the findings and models developed make this pilot tool easily scalable to the US. The lessons learned during the design, implementation, and testing stages have helped find trade-off solutions to software and hardware challenges related to implementing 3D models in online tools. Green software strategies has been successfully applied to the design and operations of the tool, and the team has researched the aspects of the (non-technical) user experience that will make commercial developments of this tool even more impactful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Novel Composites for Wing and Fuselage Applications

Design development was successfully completed for textile preforms with continuous cross-stiffened epoxy panels with cut-outs. The preforms developed included 3-D angle interlock weaving of graphite structural fibers impregnated by resin film infiltration (RFI) and shown to be structurally suitable under conditions requiring minimum acquisition costs. Design guidelines/analysis methodology for such textile structures are given. The development was expanded to a fuselage side-panel component of a subsonic commercial airframe and found to be readily scalable. The successfully manufactured panel was delivered to NASA Langley for biaxial testing. This report covers the work performed under Task 3 -- Cross-Stiffened Subcomponent; Task 4 -- Design Guidelines/Analysis of Textile-Reinforced Composites; and Task 5 -- Integrally Woven Fuselage Panel.

Suarez, J. A.↗

Medical Data Architecture Capabilities and Design

Mission constraints will challenge the delivery of medical care on a long-term, deep space explorationmission. This type of mission will be restricted in the availability of medical knowledge, skills, procedures and resourcesto prevent, diagnose, and treat in-flight medical events. Challenges to providing medical care are anticipated, includingresource and resupply constraints, delayed communications and no ability for medical evacuation. The Medical DataArchitecture (MDA) project will enable medical care capability in this constrained environment.The first version of thesystem, called Test Bed 1, includes capabilities for automated data collection, data storage and data retrieval to provideinformation to the Crew Medical Officer (CMO). Test Bed 1 seeks to establish a data architecture foundation and developa scalable data management system through modular design and standardized interfaces. In addition, it will demonstrateto stakeholders the potential for an improved, automated, flow of data to and from the medical system over the currentmethods employed on the International Space Station (ISS). It integrates a set of external devices, software andprocesses, and a Subjective, Objective, Assessment, and Plan (SOAP) note commonly used by clinicians. Medical datalike electrocardiogram plots, heart rate, skin temperature, respiration rate, medications taken, and more are collectedfrom devices and stored in the Electronic Medical Records (EMR) system, and reported to crew and clinician. Devicesintegrated include the Astroskin biosensor vest and IMED CARDIAX electrocardiogram (ECG) device with INEED MDECG Glove, and the NASA-developed Medical Dose Tracker application.The system is designed to be operated as astandalone system, and can be deployed in a variety of environments, from a laptop to a data center. The system isprimarily composed of open-source software tools, and is designed to be modular, so new capabilities can be added. Thesoftware components and integration methods will be discussed.

Exploration medical system↗

Starling1 - Mission Technologies Overview

The Starling series of demonstration missions will test technologies required to achieve affordable, distributed spacecraft ("swarm") missions that: are scalable to at least 100 spacecraft for applications that include synchronized multipoint measurements; involve closely coordinated ensembles of two or more spacecraft operating as a single unit for interferometric, synthetic aperture, or similar sensor architectures; or use autonomous or semi-autonomous operation of multiple spacecraft functioning as a unit to achieve science or other mission objectives with low-cost small spacecraft.Starling1 will focus on developing technologies that enable scalability and deep space application. The mission goals include the demonstration of a Mobile Ad-hoc NETwork (MANET) through an in-space communication experiment, vision based relative navigation through the Starling Formation-flying Optical eXperiment (StarFOX), and demonstration of autonomous spacecraft reconfiguration using technologies developed by the Distributed System Autonomy (DSA) project.

Cannon, Howard↗

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Ward, Laura (ORCID:0000000345501581)↗

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗

Advanced Mirror Technology Development (AMTD) Project: 3.0 Year Status

Advanced Mirror Technology Development (AMTD) is a funded NASA Strategic Astrophysics Technology project. Begun in 2011, we are in Phase 2 of a multi-year effort. Our objective is to mature towards TRL6 critical technologies needed to produce 4-m or larger flight-qualified UVOIR mirrors by 2018 so that a viable astronomy mission can be considered by the 2020 Decadal Review. The developed technology must enable missions capable of both general astrophysics and ultra-high contrast observations of exoplanets. Just as JWST's architecture was driven by launch vehicle, a future UVOIR mission's architecture (monolithic, segmented or interferometric) will depend on capacities of future launch vehicles (and budget). Since we cannot predict the future, we must prepare for all potential futures. Therefore, we are pursuing multiple technology paths. AMTD uses a science-driven systems engineering approach. We mature technologies required to enable the highest priority science AND result in a high-performance low-cost low-risk system. One of our key accomplishments is that we have derived engineering specifications for advanced normal-incidence monolithic and segmented mirror systems needed to enable both general astrophysics and ultra-high contrast observations of exoplanets missions as a function of potential launch vehicle and its inherent mass and volume constraints. Another key accomplishment is that we have matured our technology by building and testing hardware. To demonstrate stacked core technology, we built a 400 mm thick mirror. Currently, to demonstrate lateral scalability, we are manufacturing a 1.5 meter mirror. To assist in architecture trade studies, the Engineering team develops Structural, Thermal and Optical Performance (STOP) models of candidate mirror assembly systems including substrates, structures, and mechanisms. These models are validated by test of full- and subscale components in relevant thermo-vacuum environments. Specific analyses include: maximum mirror substrate size, first fundamental mode frequency (i.e., stiffness) and mass required to fabricate without quilting, survive launch, and achieve stable pointing and maximum thermal time constant.

Stahl, H. Philip↗

Hardware Fuzzing with An Emulator

Bugs in digital logic have led to some significant security vulnerabilities. Hardware bugs are particularly troublesome since they cannot be easily patched. Additionally, if the bug is in the root of trust, all trust built upon it can be vulnerable. Traditional testing either require a deep knowledge of the system, creative attack vectors and lots of human interaction. This is not scalable as there are very few engineers that can wear the hat of a designer, a verification engineer, and a cybersecurity expert. Hardware fuzzing is a relatively new research area in dynamic hardware testing. It has proven to be an effective method for discovering bugs, unexpected behaviors, and security vulnerabilities in software. While hardware fuzzing is new to the hardware domain, it has a strong track record in software testing. Fuzzing is a testing technique that randomly mutates the input data to uncover bugs or vulnerabilities in the design. It is especially good at finding corner cases that test engineers can not envision. Another advantage over other dynamic testing techniques is that, if done well, deep knowledge of the design is not required. Additionally, fuzzing scales well. If the system is set up correctly, it can run unsupervised for weeks if necessary. In this work, we propose using hardware fuzzing to improve the input vector generation for an information flow tracking tool. To get reasonable throughput of test vectors, an emulator is targeted as the execution platform. Efficient emulator execution has some specific requirements.

42 ENGINEERING↗

Hierarchical Flexibility Offering Strategy for Integrated Hybrid Resources in Real-time Energy Markets

This paper proposes a hierarchical model for determining the energy flexibility offering strategy of integrated hybrid resources (IHRs) in power distribution systems to participate in real-time energy markets. The proposed model utilizes the scalability, fast response time, and uncertainty observation of deep reinforcement learning (DRL) to overcome the scalability issue of operating numerous flexible resources and deliverability of energy flexibility to the real-time markets in the presence of the network constraints. To that end, the power distribution system is divided into multiple IHRs, where different types of flexible loads, energy storage systems, and solar plants with controllable inverters are operated through local IHR controllers, trained by deep deterministic policy gradient (DDPG) algorithm. Active power request and reactive power capacity of IHRs are then transmitted to a central flexibility controller, where a quadratic optimization model ensures the deliverability of the energy flexibility to the real-time energy market by satisfying the distribution network constraints. The proposed model is implemented on the 123-bus test power distribution system, demonstrating the capability of DRL-based hierarchical model for scalable operation of IHRs in order to offer deliverable energy flexibility to the real-time energy market.

Majidi, Majid↗

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing

In many neuromorphic workflows, simulators play a vital role for important tasks such as training spiking neural networks, running neuroscience simulations, and designing, implementing, and testing neuromorphic algorithms. Currently available simulators cater to either neuroscience workflows (e.g., NEST and Brian2) or deep learning workflows (e.g., BindsNET). Problematically, the neuroscience-based simulators are slow and not very scalable, and the deep learning-based simulators do not support certain functionalities that are typical of neuromorphic workloads (e.g., synaptic delay). In this paper, we address this gap in the literature and present SuperNeuro, which is a fast and scalable simulator for neuromorphic computing capable of both homogeneous and heterogeneous simulations as well as GPU acceleration. We also present preliminary results that compare SuperNeuro to widely used neuromorphic simulators such as NEST, Brian2, and BindsNET in terms of computation times. We demonstrate that SuperNeuro can be approximately 10×--300× faster than some of the other simulators for small sparse networks. On large sparse and large dense networks, SuperNeuro can be approximately 2.2×--3.4× faster than the other simulators, respectively.

Date, Prasanna↗

Ceramic high temperature receiver design and tests

The High Temperature Solar Thermal Receiver, which was tested a Edwards AFB, CA during the winter of 1980-1981, evolved from technologies developed over a five year period of work. This receiver was tested at the Army Solar Furnace at White Sands, NM in 1976. The receiver, was tested successfully at 1768 deg F and showed thermal efficiencies of 85%. The results were sufficiently promising to lead ERDA to fund our development and test of a 250 kW receiver to measure the efficiency of an open cavity receiver atop a central tower of a heliostat field. This receiver was required to be design scalable to 10, 50, and 100 MW-electric sizes to show applicability to central power tower receivers. That receiver employed rectagular silicon carbide panels and vertical stanchions to achieve scalability. The construction was shown to be fully scalable; and the receiver was operated at temperatures up to 2000 deg F to achieve the performance goals of the experiment during tests at the GIT advanced components test facility during the fall of 1978.

Davis, S. B.↗

Scalable Detector Design for a High-Resolution Fast-Neutron Radiography Panel

Development of a scalable flat-panel neutron radiography device is needed to meet the nondestructive testing needs of a growing industrial market. Flood field images from a Cs-137 gamma source and a Cf-252 fission neutron source were generated using a detector composed of a 3-mm-thick sheet of EJ-200, and 3-mm-thick sheet of acrylic light spreader, an 8 $\times$ 8 array of SensL MICROFJ-60035-TSV SiPMs, and an IDEAS ROSSPAD readout module. The readout module can be tiled together with similar systems to create a panel of any size, and is only limited by the number of available Ethernet ports in a switching system. A collimated gamma line image demonstrated a 90% spatial resolution of approximately 0.47 line pairs per centimeter and a 10% spatial resolution of approximately 2.32 line pairs per centimeter. A neutron edge image demonstrated a 90% spatial resolution of approximately 0.70 line pairs per centimeter and a 10% spatial resolution of approximately 3.35 line pairs per centimeter. Both of these images show the ability to generate radiographs with sub-SiPM spatial resolution. Using these readout modules, a large-scale radiographic panel can be developed by tiling ROSSPAD modules together.

36 MATERIALS SCIENCE↗

Dynamic load balancing with enhanced shared-memory parallelism for particle-in-cell codes

Furthering our understanding of many of today’s interesting problems in plasma physics – including plasma based acceleration and magnetic reconnection with pair production due to quantum electrodynamic effects – requires large-scale kinetic simulations using particle-in-cell (PIC) codes. However, these simulations are extremely demanding, requiring that contemporary PIC codes be designed to efficiently use a new fleet of exascale computing architectures. To this end, the key issue of parallel load balance across computational nodes must be addressed. We discuss the implementation of dynamic load balancing by dividing the simulation space into many small, self-contained regions or ‘‘tiles,’’ along with shared-memory (e.g., OpenMP) parallelism both over many tiles and within single tiles. The load balancing algorithm can be used with three different topologies, including two space-filling curves. Here, we tested this implementation in the code Osiris and show low overhead and improved scalability with OpenMP thread number on simulations with both uniform load and severe load imbalance. Compared to other load-balancing techniques, our algorithm gives order-of-magnitude improvement in parallel scalability for simulations with severe load imbalance issues.

97 MATHEMATICS AND COMPUTING↗

Ultralow Voltage GaN Vacuum Nanodiodes in Air

The III-nitride semiconductors have many attractive properties for field-emission vacuum electronics, including high thermal and chemical stability, low electron affinity, and high breakdown fields. In this work, we report top-down fabricated gallium nitride (GaN)-based nanoscale vacuum electron diodes operable in air, with record ultralow turn-on voltages down to ~0.24 V and stable high field-emission currents, tested up to several microamps for single-emitter devices. We leverage a scalable, top-down GaN nanofabrication method leading to damage-free and smooth surfaces. Gap-dependent and pressure-dependent studies provide new insights into the design of future, integrated nanogap vacuum electron devices. The results show promise for a new class of high-performance and robust, on-chip, III-nitride-based vacuum nanoelectronics operable in air or reduced vacuum.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. 2. Quantifying the Uncertainty

Uncertainty quantification of groundwater (GW) aquifer parameters is critical for efficient management and sustainable extraction of GW resources. These uncertainties are introduced by the data, model, and prior information on the parameters. We develop a Bayesian inversion framework that uses Interferometric Synthetic Aperture Radar (InSAR) surface deformation data to infer the laterally heterogeneous permeability of a transient linear poroelastic model of a confined GW aquifer. The Bayesian solution of this inverse problem takes the form of a posterior probability density of the permeability. Exploring this posterior using classical Markov chain Monte Carlo (MCMC) methods is computationally prohibitive due to the large dimension of the discretized permeability field and the expense of solving the poroelastic forward problem. However, in many partial differential equation (PDE)-based Bayesian inversion problems, the data are only informative in a few directions in parameter space. For the poroelasticity problem, we prove this property theoretically for a one-dimensional problem and demonstrate it numerically for a three-dimensional aquifer model. Here we design a generalized preconditioned Crank-Nicolson (gpCN) MCMC method that exploits this intrinsic low dimensionality by using a low-rank-based Laplace approximation of the posterior as a proposal, which we build scalably. The feasibility of our approach is demonstrated through a real GW aquifer test in Nevada. The inherently two-dimensional nature of InSAR surface deformation data informs a sufficient number of modes of the permeability field to allow detection of major structures within the aquifer, significantly reducing the uncertainty in the pressure and the displacement quantities of interest.

54 ENVIRONMENTAL SCIENCES↗

HydraGNN 2.0

HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission. New or improved capabilities included in v2.0.0 release are as follows: 1) Enhancement in message passing layers through class inheritance 2) Adding transformation to ensure translation and rotation invariance 3) Supporting various optimizers 4) Atomic descriptors 5) Integration with continuous CI test 6) Distributed printouts and timers 7) Profiling 8) Support of ADIOS2 for scalable data loading 9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗