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At least 523 records · Page 29

Autonomous Anomaly Detection for MPC Forecasts of HVAC Systems in Residential Communities

The use of residential heating, ventilation, and air conditioning (HVAC) to shift peak demand or provide ancillary services is a potential solution in the presence of older grids and distributed renewables. However, to ensure the efficient use of devices, utilities need to accurately forecast the load and adopt error correction schemes when necessary. While significant theoretical research exists in the area of predictive control of HVAC, little experimental evidence exists. The lack of experimental data in turn causes researchers to be unprepared for unsystematic errors which emerge due to the higher complexity of the data generating process. This study offers an anomaly detection methodology that uses unsupervised machine learning algorithms to detect and isolate these errors with different forecast error ranges. The results of anomaly detection procedure can then be used for error correction and would eventually help develop better predictive controllers. The methodology is tested using real world data from a smart neighborhood that currently operates in Atlanta. GA.

Lebakula, Viswadeep↗

First Moments of a Polyhedron Clipped by a Paraboloid

We provide closed-form expressions for the first moments (i.e., the volume and volume-weighted centroid) of a polyhedron clipped by a paraboloid, that is, of a polyhedron intersected with the subset of the three-dimensional real space located on one side of a paraboloid. These closed-form expressions are derived following successive applications of the divergence theorem and the judicious parametrization of the intersection of the polyhedron’s faces with the paraboloid. Here, we provide means for identifying ambiguous discrete intersection topologies, and propose a corrective procedure for preventing their occurence. Finally, we put our proposed closed-form expressions and numerical approach to the test with millions of random and manually engineered polyhedron/paraboloid intersection configurations. The results of these tests show that we are able to provide robust machine-accurate estimates of the first moments at a computational cost that is within one order of magnitude of that of state-of-the-art half-space clipping algorithms.

97 MATHEMATICS AND COMPUTING↗

Quality-Controlled Meteorological Data from the Flood Control District of Maricopa County (FCDMC) Network, Phoenix, Arizona (1987-2024)

This dataset contains 15- or 30-minute interval meteorological data from the Flood Control District of Maricopa County (FCDMC), Arizona, USA, covering eight key variables across multiple sensor stations between 1987 and 2024. Each variable is stored as a separate CSV file, containing time-series data that have undergone rigorous quality control (QC) procedures and, where appropriate, short-gap interpolation for consistency. The quality control (QC) pipeline consisted of four sequential tests: (1) a range test to ensure all values fall within physically realistic limits, (2) a step test to identify abrupt and implausible changes between consecutive records, (3) a proximity test that validates flagged values from step test using data from nearby stations and exceedance probability thresholds, and (4) a persistence test to detect and remove periods of unrealistically constant readings. These thresholds were calibrated to Arizona’s environmental conditions and sensor specifications. After QC, short gaps (≤2 hours) were linearly interpolated to ensure consistent temporal resolution, except for wind variables. Due to a major upgrade in FCDMC’s data transmission system, only ALERT-2 protocol data (2016–2024) for wind variables are included; earlier ALERT-1 data were excluded because of irregular sampling and high missing rates. This dataset supports regional climate and infrastructure resilience studies by providing standardized, high-resolution meteorological data for the greater Phoenix metropolitan area.

54 ENVIRONMENTAL SCIENCES↗

First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska North Slope – Producer Responses and Operational Lessons Learned

The US Department of Energy and Hilcorp Alaska, LLC are jointly cosponsoring a field pilot project entitled “First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil Enhanced Oil Recovery (EOR).” The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on Alaska North Slope (ANS). Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot which was designed to acquire field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Hydrolyzed polyacrylamide (HPAM) polymer injection started on August 28, 2018 using a custom made polymer mixing and pumping unit. Polymer solution properties such as concentration, viscosity, and filter ratio, have been closely monitored and adjusted as necessary. Operational procedures have been improved to ensure adequate injectivity and polymer propagation through the formation. Oil and water production is tested frequently to monitor water cut performance, and produced water is sampled and analyzed for polymer content. Tracers were pumped pre and post polymer injection startup to compare polymer flood breakthrough timing and sweep efficiency. Polymer injectivity of the horizontal wells drilled in the Schrader Bluff NB sand is found to be sufficient to replace the reservoir production voidage although there were some declines as high viscosity polymer swept the near wellbore region. Production data show significant reduction in water cut and the oil production rate has stabilized. No polymer production has been confirmed from the two horizontal producers after 22 months of polymer injection into the two supporting horizontal injectors. Tracer data show very low sweep efficiencies with waterflood alone, whereas significant improvement has been achieved with polymer flood. Many operational lessons have been learned and improvements have been made regarding polymer mixing, pumping, and onsite quality control, particularly in a challenging Arctic environment. Adequate polymer injection rate can be achieved with diligent monitoring and quality assurance of the properties of the injected polymer solution.

Ning, Samson↗

Characterization and CST Batch Contact Equilibrium Testing of Modified Tank 9H Process Supernate Samples in Support of TCCR

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with crystalline silicotitanate (CST) media to process radioactive waste solutions for the removal of ¹³⁷Cs. TCCR currently focuses on dissolving Savannah River Site (SRS) radioactive tank waste (primarily sodium saltcake solids) within Tank 10H followed by at-tank ion exchange column treatment. Two supernate batches from Tank 10H have been processed through the TCCR unit and processing of a third batch is expected soon. After processing of this supernate batch, plans are to replace the CST columns and process dissolved salt solution from Tank 9H through Tank 10H and then through the new CST columns installed in the TCCR unit. The new columns are expected to contain either a media similar to an archived CST batch (IE-911) or the R9120-B CST media used in the current TCCR columns (the two materials are fundamentally the same; just different specifications, product names, and preconditioning steps). Samples of Tank 9H dissolved saltcake were received at the Savannah River National Laboratory (SRNL) and characterized. The Tank 9H supernate contained a high sodium concentration (~9.6 M Na⁺) and will require dilution to near 6 M [Na⁺] prior to processing through the TCCR unit. The cesium concentration in Tank 9H is currently significantly higher than was observed with Tank 10H. Three dilutions of the Tank 9H supernate were conducted to mimic possible dilutions that could be conducted in the tank farm prior to TCCR processing using inhibited water, sodium hydroxide, and sodium nitrate solutions. Dilution #1 was prepared by diluting the Tank 9H supernate by a factor of 1.6 with inhibited water, Dilution #2 was prepared by diluting the Tank 9H supernate by a factor of 3.7 with a mixed sodium hydroxide/sodium nitrate diluent, and Dilution #3 was prepared by also diluting by a factor of 3.7 but with sodium hydroxide only. All three dilutions have similar Na⁺ concentrations (~6 M), but Dilutions #2 and #3 contain significantly less cesium. Major and key minor components of the diluted Tank 9H supernate samples are provided in Table ES-1. Batch contact equilibrium tests were conducted with the Tank 9H dilutions and the two different CST media batches being considered for use in the new TCCR columns. Results are summarized in Table ES-2 and compared to ZAM model predictions. The highest cesium distribution coefficient and percent removal were observed with Dilution #3. IE-911 CST (an archived CST media batch) was more effective at removing cesium than the more recently prepared R9120-B CST media, though both media samples removed >88% of the cesium and the differences may not be statistically different considering the overall uncertainty. Based on the results, maximum cesium loadings were calculated for each CST media type and Tank 9H dilution. In general, maximum cesium loadings from dilutions of this supernate batch are quite high (approaching 0.1 mmol total Cs⁺/g CST for Dilution #1). The highest calculated maximum ¹³⁷Cs loading for the Tank 9H dilutions using the ZAM model with input of the tank compositions and batch contact results was 207 Ci/kg CST (Dilution #1 with IE-911 CST). In all cases, higher maximum cesium loading values were predicted for IE-911 CST versus R9120-B, although the differences varied considerably between the dilutions. The maximum loading value for IE-911 CST with Tank 9H Dilution #1 was only 7% higher than the maximum loading for R9120-B. The maximum loading value for IE-911 CST with Dilution #3 was 24% higher than the maximum loading for R9120-B. Dilution #2 was intermediate between these values. Note that these maximum loading values are the theoretical calculated values, and actual operating conditions will cause differences. A CST binder dilution (correction) factor near 0.7 (relative to pure powder CST) was required for each batch contact test with IE-911 engineered CST using the three Tank 9H dilutions. Correction factors calculated for R9120-B CST ranged from 0.56 to 0.66 for the three dilutions. Following the batch contact tests, the CST samples were isolated from the Tank 9H solution, washed, dried, and digested in acid following established procedures. The analysis results are provided in Table ES-3. Total cesium loading values determined by CST digestion were similar to the calculated loading values based on solution analysis (Table ES-2) for all samples. In addition, the CST was observed to load calcium (R9120-B sample only), iron, strontium, lead, uranium, and plutonium after contact with the waste supernate, as has been observed previously.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Empirical Formula for Puncture Energy of Flat Metal Plates by a Cylindrical Flat Punch

Impact problems of plate-like parts by punch-like objects with relatively large mass moving at slow speeds of a few feet per second constitute a subset of impact problems of interest at Sandia. This is in contrast to small objects moving in the range of hundreds or thousands of feet per second or higher. The objective of this work is to develop a simple formula that can be used to estimate a lower bound for the puncture energy of metal plates impacted by cylindrical, essentially rigid punches of circular cross-section and at nose. Such geometry is used as a basis in the design of puncture mitigation barriers or procedures. This was accomplished by deriving an expression using non-dimensional analysis and then calibrating it based on tests results in the range of speeds of interest. Lower bounds can then be determined based on confidence intervals or factors of safety.

36 MATERIALS SCIENCE↗

Drop C: The Drop-In, Ring-of-Power Heliostat (Final Report)

This report summarizes the work performed within the Drop-C: The Drop-In, Ring-of-Power Heliostat project. The Drop-C project aimed to develop a novel heliostat with an installed cost of $\$50$/m 2 ($\$2015$) which is a drastic cost reduction compared to the state-of-the-art. The resulting 27m 2 SunRing TM heliostat’s relative small size necessitates the parallel development of a wireless solar field network and a rapid calibration system. The SunRing heliostat is an evolution of the Ring-of-Power (ROP) design from Abengoa Solar LLC which had a reported installed cost of $114/m 2 . Cost savings relative to the ROP were sought by increasing the mirror area, improving the structural efficiency, a more accurate assessment of wind loads, and an improved assembly and installation procedure. The project spanned three Budget Periods (BP) where a digital heliostat was developed in BP1 using wind tunnel testing to define load conditions.

14 SOLAR ENERGY↗

Direct Feed High-Level Waste APPS Model Glass Testing (DFHLW APPS) Matrix, Phase 2

This report summarizes the data collected during the batching and melting of a second matrix of Direct Feed High-Level Waste (DFHLW) glasses generated using the preliminary enhanced waste glass models (EWG2.5) and the Britton and Anderson (2024) preliminary DFHLW feed vector. The purpose of these glasses is two-fold: 1. Validate EWG2.5 glass calculations being used in the Aspen Process Performance Simulation (APPS) model. 2. Evaluate and ultimately improve the glass property models and formulation methods used for design of DFHLW glasses as part of an iterative process of data collection and model refinement. Some of the 16 APPS2 glasses tested did not satisfy all target property constraints due to the limited data on DFHLW glass supporting the EWG2.5 models. • One glass, APPS2-10, formed nepheline on canister centerline cooling (CCC) heat-treatment and failed the product consistency test (PCT) response limits. This glass also had high B and Cr release rates for the toxicity characteristic leaching procedure (TCLP). All other glasses were found to satisfy the PCT and TCLP constraints for both quenched and CCC samples. • One glass, APPS2-08, had higher than acceptable viscosity due to magnetite crystallization. • One glass, APPS2-09, formed greater than 2 vol% crystals at 950 °C. As the glass design criterion was that the temperature at 2 vol% crystal (T 2% ) be less than 950 °C, only one glass failed the criteria. However, this criterion is being reevaluated. Four additional glasses formed crystal fractions between 1 and 2 vol% at 950 °C (APPS2-03, -08, -12, and -14). • Four glasses – APPS2-01, -02, -04, and -16 – failed the Monofrax K-3 refractory neck corrosion (k neck ) design limit of 0.04 in. at 1208 °C for 6 d. This is another criterion being reevaluated. Four additional glasses (APPS2-05, -06, -11, and -13) exhibited 0.025 = k neck = 0.04 in. • All 16 glasses passed the sulfur solubility and TCLP constraints. The measured property values were compared to predicted values using EWG2.5 and a selection of other existing models. A few models (e.g., electrical conductivity, TCLP) were found to be adequate for designing DFHLW glasses in the near future, while others require refits or offsets. It is recommended that new property models be developed for EWG3.0, as a large amount of DFHLW glass property data (> 14 × existing data) is expected to be collected in the compositional spaces where no data was previously available. To enable near-term calculations and formulations for designing DFHLW glasses and processing rate estimations, a formulation algorithm with minor modifications will be developed, EWG2.6.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Immediate impacts of soybean cover crop on bacterial community composition and diversity in soil under long-term Saccharum monoculture

Saccharum yield decline results from long-term monoculture practices. Changes in cropping management can improve soil health and productivity. Below-ground bacterial community diversity and composition across soybean (Glycine max (L.) Merr) cover crop, Saccharum monoculture (30+ year) and fallowed soil were determined. Near full length (~1,400 base pairs) of 16S rRNA gene sequences were extracted from the rhizospheres of sugarcane and soybean and fallowed soil were compared. Higher soil bacterial diversity was observed in the soybean cover crop than sugarcane monoculture across all measured indices (observed operationational taxonomic units, Chao1, Shannon, reciprocal Simpson and Jackknife). Acidocateria, Proteobacteria, Bacteroidetes and Planctomycetes were the most abundant bacterial phyla across the treatments. Indicator species analysis identified nine indicator phyla. Planctomycetes, Armatimonadetes and candidate phylum FBP were associated with soybean; Proteobacteria and Firmicutes were linked with sugarcane and Gemmatimonadetes, Nitrospirae, Rokubacteria and unclassified bacteria were associated with fallowed soil. Non-metric multidimensional scaling analysis showed distinct groupings of bacterial operational taxonomic units (97% identity) according to management system (soybean, sugarcane or fallow) indicating compositional differences among treatments. This is confirmed by the results of the multi-response permutation procedures (A = 0.541, p = 0.00045716). No correlation between soil parameters and bacterial community structure was observed according to Mantel test (r = 211865, p = 0.14). Use of soybean cover-crop fostered bacterial diversity and altered community structure. This indicates cover crops could have a restorative effect and potentially promote sustainability in long-term Saccharum production systems.

Bacterial diversity↗

A Framework to Demonstrate a DNP3 Interface With a CIM-Based Data Integration Platform: Preprint

The contemporary electrical grid is characterized by its complexity and abundance of data. A control-rich environment supported by information and communication technologies within an Advanced Distribution Management System (ADMS) presents a viable and cost-effective option for utility companies aiming to implement advanced real-time analytical schemes for monitoring and remotely controlling distribution feeders. Modular platform-based approaches to distribution operations require a structured framework for acquiring field device measurements, performing analytics, converting the setpoint to the correct protocol, and sending it on the appropriate communications network to the field devices. We present the development and deployment of an application service to integrate an open-source standardsbased platform with an ADMS test bed with field devices using the Distributed Network Protocol (DNP3) for data exchange. The step-by-step procedure for establishing the DNP3-Master service on an open-source distribution platform is outlined, comprehensively explaining the Master setup process. Moreover, sample use case results highlight the capabilities of the DNP3- Master service setup. Results demonstrate the scalability and configurability of the DNP3-Master service, making it adaptable for integration with other relevant applications, thus providing potential opportunities for real-world field trials and real-time assessments.

ADMS↗

Assessing Methodologies for Detecting Water Intrusion in Wall Systems: Phase 2

Studies by the University of Florida, the Environmental Protection Agency (EPA) and the U.S. Department of Housing (HUD) have revealed that there is a substantial fraction of commercial and residential buildings that have been exposed to moisture resulting in damage or durability problems. Water intrusion into building envelope components leads to a variety of undesirable conditions such as mold, wood rot, corrosion, and aesthetic damage. Tests methods that are presently used to evaluate the amount of water intrusion into a building envelope component are usually qualitative in nature. For example, ASTM E 331, Standard Test Method for Water Penetration of Exterior Windows, Curtain Walls, and Doors by Uniform Static Air Pressure Difference requires that you “observe and record points of water leakage, if any.” This test was originally developed to assess the performance of fenestration products but is commonly adapted to evaluate other enclosure assemblies. However, when it is typically used for walls, this procedure is limited to recognizing if the moisture is visually observable from the backside side of the sheathing. It does not address moisture that is absorbed in the layers of the building envelope component, which could impact the durability of the assembly. Clearly a quantitative means of determining water penetration would improve the quality of this type of test and assist with better understanding the resultant impact on enclosure assemblies. In 2018-20, Oak Ridge National Laboratory, in conjunction with the Air Barrier Association of America, initiated a research project to address this issue. The purpose of that study was to evaluate nine different methods of detecting moisture intrusion through a wall assembly. air and water barrier. The wall assemblies included metal frame construction faced with gypsum sheathing and both self-adhered and fluid applied air and water barriers (AWB) were evaluated for this exercise. This project did not test the efficacy of the different AWBs, rather, fasteners were purposely installed in various ways to foster water penetration and activate the different methods of detection. Each detection method was evaluated for five features that included simplicity of use, cost of implementation, whether the method was quantitative or subjective, accuracy, and applicability. A scale of green/yellow/red was used to assess each feature where green was acceptable, yellow was borderline, and red was not to be pursued at this time. This report covers additional research that has been undertaken to extend the activities initiated in this earlier project with refinements for specific detection methods and considerations for expansion related to field versus laboratory testing standards.

42 ENGINEERING↗

The CMS Phase 2 Outer Tracker Analyzer of Test Outputs - POTATO!

The Phase-2 upgrade of the Large Hadron Collider (LHC), also known as the High-Luminosity LHC (HL-LHC) is designed to achieve peak instantaneous luminosities which is about an order of magnitude higher than the nominal design value of $10^{34}~cm^{-2}s^{-1}$ delivering a total of atleast $3000 fb^{-1}$ data over 10 years of operation at $\sqrt{s}~=~14~TeV$. One crucial aspect of the CMS Phase-2 detector upgrade is the replacement of the existing tracking detector in order to deal with the extreme HL-LHC conditions, retaining and further expanding the physics performances achieved in the previous years. The outer part of the upgraded tracker (OT), will be equipped with over 13,000 macro Pixel-Strip (PS) and Strip-Strip (2S) modules! Module production is distributed across centers worldwide and necessitates coordinated efforts and standardized procedures. Along with production and assembly of the modules, Fermilab OT group is also working on a tool, Phase 2 Outer Tracker Analyzer of Test Outputs (POTATO) that will analyze, grade, upload and manage the large quantity of files to be stored in the centralized Database (DB). In this contribution a brief overview of the module testing and the power and dire need of POTATO to handle this large number of test outputs will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The CMS Phase 2 Outer Tracker Analyzer of Test Outputs - POTATO!

The Phase-2 upgrade of the Large Hadron Collider (LHC), also known as the High-Luminosity LHC (HL-LHC) is designed to achieve peak instantaneous luminosities which is about an order of magnitude higher than the nominal design value of $10^{34}~cm^{-2}s^{-1}$ delivering a total of atleast $3000 fb^{-1}$ data over 10 years of operation at $\sqrt{s}~=~14~TeV$. One crucial aspect of the CMS Phase-2 detector upgrade is the replacement of the existing tracking detector in order to deal with the extreme HL-LHC conditions, retaining and further expanding the physics performances achieved in the previous years. The outer part of the upgraded tracker (OT), will be equipped with over 13,000 macro Pixel-Strip (PS) and Strip-Strip (2S) modules! Module production is distributed across centers worldwide and necessitates coordinated efforts and standardized procedures. Along with production and assembly of the modules, Fermilab OT group is also working on a tool, Phase 2 Outer Tracker Analyzer of Test Outputs (POTATO) that will analyze, grade, upload and manage the large quantity of files to be stored in the centralized Database (DB). In this contribution a brief overview of the module testing and the power and dire need of POTATO to handle this large number of test outputs will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory (BMS and RMS SOP)

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory: 2024 Edition

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility. This 2024 edition includes updates to the appendices to reflect the instrument changes from one year to another.

14 SOLAR ENERGY↗

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory: 2025 Edition

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility. This 2025 edition includes updates to the appendices to describe the current instrumentation of the NREL-SRRL.

14 SOLAR ENERGY↗

Hybrid geological modeling: Combining machine learning and multiple-point statistics

Accurately modeling and constructing a geologically realistic subsurface model remains an outstanding problem as the morphology controls the flow behaviors. Particularly, one of the pattern-based methods, namely cross-correlation based simulation, has been proved to be an effective way to reconstruct a realistic model, at both small and large scales. However, conditioning to point data in the large-scale problems is still a crucial issue in these algorithms, since there is always a trade-off between the quality of the realizations and the degree of point data reproduction. Specifically, it is not practical to build a training image (TI) which includes all the possibilities and variabilities. Therefore, finding a pattern that can represent the point data and, at the same time, preserving the connectivities is difficult. This leads to producing highly-connected realizations with a significant mismatch or poor models with a reasonable degree of point data reproduction. To accurately reproduce the densely distributed hard data, pixel-based methods can also produce some unrealistic artifacts around the hard data. In this paper, to overcome this challenge, however, we use pattern-based methods as they often produce more disconnected geobodies when dealing with dense hard data, and proposed a hybrid algorithm using the pattern-based methods and convolutional neural network (CNN). The trained CNN model is utilized to improve the quality of conditioning to point data for the original realizations generated by the pattern-based algorithm. As such, the mismatch locations are identified, and the same regions are used in the training of CNN to mimic the procedure through which a missing region can be filled. To evaluate the performance of the proposed hybrid algorithm, it is tested on cases with different dimensions and different numbers of facies. Then, the newly improved realizations are compared with the initial realizations generated by the pattern-based algorithm. The comparison is also conducted by the flow simulation test. And it indicates that the proposed hybrid algorithm can better reproduce the point data, while the connectivities are better preserved.

58 GEOSCIENCES↗

Quantification of manganese for ChemCam Mars and laboratory spectra using a multivariate model

In this work, we report a new calibration model for manganese using the laser-induced breakdown spectroscopy instrument that is part of the ChemCam instrument suite onboard the NASA Curiosity rover. The model has been trained using an expanded set of 523 manganese-bearing rock, mineral, metal ore, and synthetic standards. The optimal calibration model uses the Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection Operator (LASSO) multivariate techniques, with a novel “double blending” technique. We determined the detection limit for manganese is 82 ppm using a method blank procedure and is possibly as low as 27 ppm based on visual inspection of the spectra. Based on a representative test set consisting of measurements on 93 standards, the double blended multivariate model shows a Root Mean Squared Error of Prediction (RMSEP) accuracy of 1.39 wt% MnO for the full blended model. Employing a local RMSEP estimate where the model performance is evaluated based on nearby test samples, the accuracy is 0.03 wt% at the quantification limit (0.05 wt% MnO), 0.4 wt% accuracy at 1.0 wt% MnO, and 4.4 wt% accuracy at 100 wt% MnO. Precision is estimated using the standard deviation of the test set measurements, and is ±0.01 wt% MnO at the quantification limit, ±0.09 wt% MnO at 1.0 wt% MnO, and ± 2.1 wt% MnO at 100 wt% MnO (all 1 standard deviation). This new calibration is important for understanding the variation of manganese in the bedrock with the Curiosity rover on Mars, which provides insight into past redox conditions on Mars.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗