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At least 721 records · Page 40

The Importance of Contamination Knowledge - Insights into Mars Sample Return

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (JSC), in Houston, TX (henceforth Curation Office) manages the curation of all past, present, and future extraterrestrial samples returned by NASA missions and shared collections from international partners, preserving their integrity for future scientific study while providing the samples to the international community in a fair and unbiased way. The Curation Office also curates all reference and witness materials for each mission (e.g., flight and non-flight hardware coupons; lubricants; non-flight, flight-like, and flown witness plates). These reference and witness materials provide the scientific community with the fundamental ability to reconstruct the contamination/alteration history of the sample collection through the course of the mission, with the overall goal of strengthening the scientific conclusions drawn from the study of returned materials. The information gained from characterizing the physical, biological, inorganic, and organic chemical properties of reference and witness materials is defined as the Contamination Knowledge (CK) of the sample collection. Unlike the data collected for Contamination Control (CC) and Planetary Protection (PP), CK is exclusively concerned with preserving reference and witness materials for study by future scientists upon sample return. Although CC and PP data collected for sample integrity and forward contamination purposes can be complementary to CK, they are two separate data sets with distinct objectives. A robust collection of samples for CK is necessary to allow the extraterrestrial material in a returned sample to be distinguished from terrestrial contamination. Traditionally CK is utilized by sample scientists in order to accomplish the mission’s scientific objectives, however this information can also be utilized by the Office of Planetary Protection to help evaluate the presence of any back contamination. Mars 2020, the first phase of a potential multipart Mars Sample Return (MSR) campaign, is expected to contribute to NASA’s Mars Exploration Program Science Goals by filling in knowledge gaps concerning: 1) the existence of past or present life on Mars, 2) the past and present climate of Mars, 3) the geology of Mars, and 4) hazards associated with human exploration of Mars. Although there is debate concerning which samples will best answer these questions, the necessity for proper sample blanks is well-understood. The CC and PP requirements, driven by the restricted Class V mission designation, are the most stringent of any sample return mission in recent history. The extremely low levels of allowable terrestrial contamination on the spacecraft and rover can complicate these analyses given the detection limits of current analytical instrumentation, especially in the case of biological contamination. By collecting and curating unanalyzed samples specifically for CK, future sample scientists will not be relegated to: 1) relying on data collected using possibly obsolete tools and techniques for return sample blanks, or 2) using remnants of extracted and/or cultured samples from ATLO (Assembly, Test, and Launch Operations), which could be incompatible with the desired experimental endpoints or state-of-the-art techniques available at the time of sample return.The addition of biological experimental endpoints to a sample return campaign’s objectives broadens the requisite range in preservation environments (e.g. inert ultra-pure nitrogen gaseous environment at 18 degrees Centigrade versus less than or equal to minus 80 degrees Centigrade) and types of CK samples. As a result, the Curation Office will also curate the following CK samples at less than or equal to minus 80 degrees Centigrade for the Mars 2020 mission: 1) unanalyzed swabs and wipes in sterile containers, 2) all recirculation filters from the clean rooms used for sample and caching subsystem assembly and all filters from the laminar flow benches used to assemble sample intimate hardware, and 3) witness plates collecting airborne contamination within the assembly clean rooms. It has been Curation Office policy since the Apollo missions to preserve as many pristine samples as possible for future scientific research. Although CK is required to be collected for all stages of the MSR campaign, the CK for the Mars 2020 mission is the most critical for understanding contamination in the returned samples given the intimacy between the Martian samples and the Mars 2020 flight hardware. This presentation highlights the importance of CK for sample return missions as well as the traditional and novel types of CK samples required for a successful MSR campaign.

Harrington, A. D.↗

Real Time Nitrogen Monitoring and Quality Control System for NASA Astromaterials Collection

The Nitrogen system is a vital utility supporting the curation office within NASA's Astromaterials Re-search and Exploration Science (ARES) Division at the Johnson Space center (JSC). Since the Apollo samples were returned in 1969. It has played an essential role in preserving NASA’s astromaterial collections (now nine collections) by maintaining contamination-free, controlled environments required for long term curation and advanced scientific research. To meet the stringent purity requirements for contamination control, high purity modified Grade C Liquid Nitrogen (LN2) is delivered weekly by an industrial gas vendor to a 15,000-gallon tank located outside at NASA JSC near the ARES facility. This nitrogen is vital for creating an inert atmosphere to store the collection in, ensuring they are continuously shielded from contaminants and alterations through a constant N2purge. For most of the past 65 years deliveries of LN2 have required a CoA (Certificate of Analysis) prior to delivery. If those were not available, then LN2 deliver were sent to third-party laboratories for verification, creating an operational bottleneck and quality gap. To address this challenge and maintain rigorous quality control, NASA JSC Infrastructure and Astromaterials Acquisition & Curation Office initiated the development of an on-site Analytical Gas Sampling (AGS) Laboratory. Designed to streamline quality verification if a CoA unavailable, the AGS lab was constructed by a subcontractor in Newton, NJ. After a successful factory acceptance test conducted by the NASA ARES Infrastructure team, the lab was trans-ported to NASA JSC, where it was anchored and integrated into the site’s nitrogen pressure system using stainless steel, oxygen-cleaned tubing. The ARES nitrogen system was modified to provide parallel flows to the AGS lab for quality control and to the astromaterials collection labs for maintaining an inert environment. The AGS lab features two operational modes: (1)Primary: Gaseous Nitrogen (GN2) Quality Monitoring –The AGS system continuously samples the site’s GN2 supply every 15 minutes to ensure compliance with required purity levels. (2) Secondary: LN2 Quality Verification when a comprehensive CoA is not available, a cryogenic vaporizer converts LN2 to GN2, which is then analyzed for impurities: H₂, Ar, O₂, CO, CO₂, H₂O, and total hydrocarbons (THC). By significantly enhancing on-site analytical capabilities, the AGS lab eliminates reliance on external testing, ensures uninterrupted quality monitoring of the nitrogen pressure system, and reinforces NASA’s commitment to preserving pristine astromaterials under the highest standards of curation and research integrity.

glove box↗

Laser Light Sheet Flow Visualization of the Space Launch System Booster Separation Test

Planar flow visualizations were obtained in a wind tunnel test in the NASA Langley Research Center’s Unitary Plan Wind Tunnel using the laser-light-sheet method. This method uses a laser to illuminate fine particles generated in the wind tunnel to visualize flow structures. The test article was designed to simulate the separation of the two solid rocket boosters (SRBs) from the core stage of the NASA Space Launch System (SLS) at Mach 4 using a scale model. The test was run on of the SLS Block 1B Cargo (27005) configuration and the SLS Block 1B Crew (28005) configuration. Planar flow visualization was obtained only on the crew configuration. Air at pressures up to 1500 psi was used to simulate plumes from the booster separation motors (BSMs) located at the nose, and aft skirt of the two boosters. The facility free stream was seeded with water vapor, which condensed and froze into small ice crystals in the tunnel nozzle expansion. A continuous wave green (532 nm) laser sheet was used to illuminate the ice crystals, and the resulting Mie-scattered light was collected with a camera. The resulting images clearly identify shock waves and other flow features including BSM plume shapes. Measurements were acquired for different BSM pressures and booster separation locations.

Danehy, Paul M.↗

Multiphysics Analyses of the Bottom Components of the 3D Printed Transformational Challenge Reactor

This research presents multi-physics analyses on the bottom components of the Transformational Challenge Reactor (TCR) facility. These components include the bottom axial reflector and the steel exit cone. The bottom axial reflector is made of pure silicon carbide elements hosting helium cooling channels These elements are 3D printed and therefore can host any arbitrary shape of the helium cooling channels. The design of the bottom reflector considers the neutronics and thermo-fluid dynamics performances as well as the manufacturing process optimization. More precisely, the best design of the bottom reflector reduces neutron leakage by avoiding straight cylindrical helium channels that facilitate neutron leakage, minimizes the helium flow pressure drop, and reduces the number of 3D printed silicon carbide pieces. The exit cone steel structure collects the hot helium from the bottom fuel assemblies and channels the cold helium to the top of the fuel assemblies. The steel simultaneous contact with hot and cold helium flows sets a large thermal gradient. Different designs of the exit cone are proposed to reduce the steel equivalent stress from the helium thermal load. The multi-physics analyses have been performed using Ansys Fluent, Ansys Mechanical, STAR-CCM+, and Serpent computer programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Observation of the Electromagnetic Field Effect via Charge-Dependent Directed Flow in Heavy-Ion Collisions at the Relativistic Heavy Ion Collider

The deconfined quark-gluon plasma (QGP) created in relativistic heavy-ion collisions enables the exploration of the fundamental properties of matter under extreme conditions. Noncentral collisions can produce strong magnetic fields on the order of 10 18 G , which offers a probe into the electrical conductivity of the QGP. In particular, quarks and antiquarks carry opposite charges and receive contrary electromagnetic forces that alter their momenta. This phenomenon can be manifested in the collective motion of final-state particles, specifically in the rapidity-odd directed flow, denoted as v 1 ( y ) . Here, we present the charge-dependent measurements of d v 1 / d y near midrapidities for π ± , K ± , and p ( p ¯ ) in Au + Au and isobar ( Ru 44 96 + Ru 44 96 and Zr 40 96 + Zr 40 96 ) collisions at s NN = 200 GeV , and in Au + Au collisions at 27 GeV, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The combined dependence of the v 1 signal on collision system, particle species, and collision centrality can be qualitatively and semiquantitatively understood as several effects on constituent quarks. While the results in central events can be explained by the u and d quarks transported from initial-state nuclei, those in peripheral events reveal the impacts of the electromagnetic field on the QGP. Our data put valuable constraints on the electrical conductivity of the QGP in theoretical calculations. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗

Molecular Rayleigh Scattering Diagnostic for Dynamic Temperature, Velocity, and Density Measurements

A molecular Rayleigh scattering technique is developed to measure dynamic gas temperature, velocity, and density in unseeded turbulent flows at sampling rates up to 16 kHz. A high power CW laser beam is focused at a point in an air jet plume and Rayleigh scattered light is collected and spectrally resolved. The spectrum of the light, which contains information about the temperature and velocity of the flow, is analyzed using a Fabry-Perot interferometer. The circular interference fringe pattern is divided into four concentric regions and sampled at 1 and 16 kHz using photon counting electronics. Monitoring the relative change in intensity within each region allows for measurement of gas temperature and velocity. Independently monitoring the total scattered light intensity provides a measure of gas density. A low speed heated jet is used to validate the measurement of temperature fluctuations and an acoustically excited nozzle flow is studied to validate velocity fluctuation measurements. Power spectral density calculations of the property fluctuations, as well as mean and fluctuating quantities are presented. Temperature fluctuation results are compared with constant current anemometry measurements and velocity fluctuation results are compared with constant temperature anemometry measurements at the same locations.

Mielke, Amy R.↗

Moving wall, continuous flow electronphoresis apparatus

This invention relates generally to electrophoresis devices and more particularly to a moving wall, continuous flow device in which an electrophoresis chamber is angularly positionable with respect to the direction of moving belt walls. A frame with an electrophoresis chamber is rotatably supported between two synchronously driven belt walls. This allows the chamber to be angularly positionable with respect to the direction of belt travel, which compensates for electroosmotic flow within the electrophoresis chamber. Injection of a buffer solution via an opening and a homogenous sample stream via another opening is performed at the end of a chamber, and collection of buffer and the fractionated species particles is done by a conventional collection array at an opposite end of the chamber. Belts are driven at a rate which exactly matches the flow of buffer and sample through the chamber, which entrains the buffer to behave as a rigid electrophoretic medium, eliminating flow distortions (Poiseuille effect). Additionally, belt material for each belt is stored at one end of the device and is taken up by drive wheels at an opposite end. The novelty of this invention particularly lies in the electrophoresis chamber being angularly positionable between two moving belt walls in order to compensate for electroosmotic flow. Additionally, new belt material is continuously exposed within the chamber, minimizing flow distortion due to contamination of the belt material by the sample.

Rhodes, Percy H.↗

Experimental study of the effects of Reynolds number on high angle of attack aerodynamic characteristics of forebodies during rotary motion

The National Aeronautics and Space Administration and the Defense Research Agency (United Kingdom) have ongoing experimental research programs in rotary-flow aerodynamics. A cooperative effort between the two agencies is currently underway to collect an extensive database for the development of high angle of attack computational methods to predict the effects of Reynolds number on the forebody flowfield at dynamic conditions, as well as to study the use of low Reynolds number data for the evaluation of high Reynolds number characteristics. Rotary balance experiments, including force and moment and surface pressure measurements, were conducted on circular and rectangular aftbodies with hemispherical and ogive noses at the Bedford and Farnborough wind tunnel facilities in the United Kingdom. The bodies were tested at 60 and 90 deg angle of attack for a wide range of Reynolds numbers in order to observe the effects of laminar, transitional, and turbulent flow separation on the forebody characteristics when rolling about the velocity vector.

Pauley, H.↗

Introduction: Prediction of F-16XL Flight Flow Physics

This special section is the result of fruitful endeavors by an international group of researchers in industry, government laboratories and university-led efforts to improve the technology readiness level of their CFD solvers through comparisons with flight data collected on the F-16XL-1 aircraft at a variety of test conditions. These 1996 flight data were documented and detailed the flight-flow physics of this aircraft through surface tufts and pressures, boundary-layer rakes and skin-friction measurements. The flight project was called the Cranked Wing Aerodynamics Project (CAWAP), due to its leading-edge sweep crank (70 degrees inboard, 50 degrees outboard), and served as a basis for the International comparisons to be made, called CAWAPI. This highly focused effort was one of two vortical flow studies facilitated by the NATO Research and Technology Organization through its Applied Vehicle Panel with a title of Understanding and Modeling Vortical Flows to Improve the Technology Readiness Level for Military Aircraft. It was given a task group number of AVT-113 and had an official start date of Spring 2003. The companion part of this task group dealt with fundamentals of vortical flow from both an experimental and numerical perspective on an analytically describable 65 degree delta-wing model for which much surface pressure data had already been measured at NASA Langley Research Center at a variety of Mach and Reynolds numbers and is called the Vortex Flow Experiment - 2 (VFE-2). These two parts or facets helped one another in understanding the predictions and data that had been or were being collected.

Lamar, John E.↗

High-Collection-Efficiency Fluorescence Detection Cell

A new fluorescence cell has been developed for the laser induced fluorescence (LIF) detection of formaldehyde. The cell is used to sample a flow of air that contains trace concentrations of formaldehyde. The cell provides a hermetically sealed volume in which a flow of air containing formaldehyde can be illuminated by a laser. The cell includes the optics for transmitting the laser beam that is used to excite the formaldehyde and for collecting the resulting fluorescence. The novelty of the cell is its small size and simple design that provides a more robust and cheaper alternative to the state of the art. Despite its simplicity, the cell provides the same sensitivity to detection as larger, more complicated cells.

Hanisco, Thomas↗

Active Flow Control on Vertical Tail Models

Active flow control (AFC) subscale experiments were conducted at the Lucas Wind Tunnel of the California Institute of Technology. Tests were performed on a generic vertical tail model at low speeds. Fluidic oscillators were used at the trailing edge of the main element (vertical stabilizer) to redirect the flow over the rudder and delay or prevent flow separation. Side force increases in excess of 50% were achieved with a 2% momentum coefficient (C(sub μ)) input. The results indicated that a collective C(sub μ) of about 1% could increase the side force by 30–50%. This result is achieved by reducing the spanwise flow on the swept back wings that contributes to early flow separation near their tips. These experiments provided the technical backdrop to test the full-scale Boeing 757 vertical tail model equipped with a fluidic oscillator system at the National Full-scale Aerodynamics Complex 40-by 80-foot Wind Tunnel, NASA Ames Research Center. The C(sub μ) is shown to be an important parameter for scaling a fluidic oscillator AFC system from subscale to full-scale wind tunnel tests. The results of these tests provided the required rationale to use a fluidic oscillator AFC configuration for a follow-on flight test on the Boeing 757 ecoDemonstrator.

Andino, Marlyn Y.↗

Turbulence-parameter estimation for current-energy converters using surrogate model optimization

Surrogate models maximize information utility by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain simulations to estimate array efficiencies and environmental impacts. Meso-scale models typically represent turbines as actuator discs that act as momentum sinks and sources of turbulence and its dissipation. An OpenFOAM model was developed where actuator disc k-ε turbulence was characterized using an approach developed for flows through vegetative canopies. Turbine-wake data from laboratory flume experiments collected at two influent turbulence intensities were used to calibrate parameters in the turbulence-source terms in the k-ε equations. Additionally, parameter influences on longitudinal wake profiles were estimated using Gaussian process regression with subsequent optimization minimizing the objective function within 3.1% of those obtained using the full model representation, but for 74% of the computational cost (far fewer model runs). This framework facilitates more efficient parameterization of the turbulence-source equations using turbine-wake data.

16 TIDAL AND WAVE POWER↗

A study of velocity, temperature, and density in the plasma generated by laser-induced breakdowns

The paper presents velocity measurements of shock-induced flow field, leading to vortex generation and plasma deformation in air. Femtosecond-laser electronic excitation tagging (FLEET) velocimetry was performed at the times Δt = 3, 20, 50, and 100 µs post laser-induced breakdown. Emissions over Δt = 3–10 µs showed the propagations of the initially elliptic shock, transitioning into a spherical front. The shock emanated along the laser axis causes the flow outward, and then the pressure gradient generated by the rarefaction wave drives the inward flow at later moments, with the velocity magnitude approaching a steady-state value of 40 m s -1 . Temporal velocity evolution was compared with non-self-similar solutions behind the propagating shock, which are sensitive to the size of the energy deposition, and the use of the measured initial plasma diameter reproduced the experiment. There establishes a region of uniform velocity around 35 m s -1 in the air-flow running through the plasma, which triggers the roll-up of the plasma surface by a large-scale vortex, providing the detail of flow field evolution from the shock propagation to the plasma deformation. A collective Thomson scattering and hybrid fs/ps pure rotational coherent anti-Stokes Raman scattering (CARS) were also performed to gain insight into the high-temperature plasma. An effective electron–ion recombination rate of 2 x 10 -12 cm 3 s -1 was measured at Δt = 0.5–10 µs, during a dynamic plasma expansion and compression. When the shock resides close to the plasma at Δt = 0.5–1 µs, the temperature distributions were found to follow the similarity law.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Financial Analysis of Experimental Releases Conducted at Glen Canyon Dam during Water Year 2021

This report was prepared by Argonne National Laboratory (Argonne) in support of a financial analysis of two Glen Canyon Dam (GCD) flow experiments that were conducted in Water Year 2021. The first experiment, called “spring disturbance flow”, was conducted from March 15 to 26, 2021. This disturbance flow experiment is designed to simulate a spring-timed runoff event so scientists can study its effects on the Colorado River ecosystem. The second experiment was a reduced and steady discharge from May 29 to June 4, 2021. This reduced steady flow experiment was conducted for the United States Geological Survey (USGS) to collect high-resolution aerial imagery over Grand Canyon National Park. This analysis was funded by the Colorado River Storage Project (CRSP) Office of the U.S. Department of Energy’s Western Area Power Administration (WAPA). CRSP markets electricity produced by hydroelectric facilities collectively known as the Salt Lake City Area Integrated Projects including dams equipped for power generation on the Colorado, Green, Gunnison, and Rio Grande Rivers and on Plateau Creek in the states of Arizona, Colorado, New Mexico, Utah, and Wyoming. Staff members in Argonne’s Energy Systems Division prepared this technical memorandum with assistance from WAPA’s CRSP and Energy Marketing and Management Offices (EMMO).

58 GEOSCIENCES↗

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling Subsurface Performance of a Geothermal Reservoir Using Machine Learning

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells—increasing or decreasing the fluid flow rates across the wells—and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy. Our computational approach allows us, first, to translate sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy, and second, to find optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an “open-source” reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 h, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 s. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs.

15 GEOTHERMAL ENERGY↗

All-metal muffler for ducts

Steel- or aluminum-skinned baffles absorb sound from air flowing over them. Because there is no bulk filler, muffler does not collect contaminants. If dirt accumulates on skin, it can be washed away without damaging muffler.

Soderman, P. T.↗