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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An empirical approach to model selection: weak lensing and intrinsic alignments

ABSTRACT In cosmology, we routinely choose between models to describe our data, and can incur biases due to insufficient models or lose constraining power with overly complex models. In this paper, we propose an empirical approach to model selection that explicitly balances parameter bias against model complexity. Our method uses synthetic data to calibrate the relation between bias and the χ2 difference between models. This allows us to interpret χ2 values obtained from real data (even if catalogues are blinded) and choose a model accordingly. We apply our method to the problem of intrinsic alignments – one of the most significant weak lensing systematics, and a major contributor to the error budget in modern lensing surveys. Specifically, we consider the example of the Dark Energy Survey Year 3 (DES Y3), and compare the commonly used non-linear alignment (NLA) and tidal alignment and tidal torque (TATT) models. The models are calibrated against bias in the Ωm–S8 plane. Once noise is accounted for, we find that it is possible to set a threshold Δχ2 that guarantees an analysis using NLA is unbiased at some specified level Nσ and confidence level. By contrast, we find that theoretically defined thresholds (based on, e.g. p-values for χ2) tend to be overly optimistic, and do not reliably rule out cosmological biases up to ∼1–2σ. Considering the real DES Y3 cosmic shear results, based on the reported difference in χ2 from NLA and TATT analyses, we find a roughly $30{{\ \rm per\ cent}}$ chance that were NLA to be the fiducial model, the results would be biased (in the Ωm–S8 plane) by more than 0.3σ. More broadly, the method we propose here is simple and general, and requires a relatively low level of resources. We foresee applications to future analyses as a model selection tool in many contexts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2009

A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis

A simple 2D M N matrix involving sample preparation enables the microanalyst to peer below the noise floor of element percentages reported by the SEM/EDX (scanning electron microscopy/ energy dispersive x-ray) analysis, thus yielding more meaningful data. Using the example of a 2 3 sample set, there are M = 2 concentration levels of the original mix under test: 10 percent ilmenite (90 percent silica) and 20 percent ilmenite (80 percent silica). For each of these M samples, N = 3 separate SEM/EDX samples were drawn. In this test, ilmenite is the element of interest. By plotting the linear trend of the M sample s known concentration versus the average of the N samples, a much higher resolution of elemental analysis can be performed. The resulting trend also shows how the noise is affecting the data, and at what point (of smaller concentrations) is it impractical to try to extract any further useful data.

Lane, John↗
DOE OSTI2020

Monte Carlo control loops for cosmic shear cosmology with DES Year 1 data

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. Monte Carlo control loops (MCCL) is a forward modeling method designed to tackle this problem. It relies on the ultra fast image generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. Here, we present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_ℓ$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, point spread function (PSF), an approximate Bayesian computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and a fast method to estimate the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a nontomographic setting, we derive a set of $C_ℓ$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $Ω_m$, $σ_8$, and intrinsic alignment amplitude $A_{IA}$, defined as $S_8D_{IA}=σ_8(Ω_m/0.3)^{0.5}D_{IA}$, where $D_{IA}=1-0.11(A_{IA}-1)$. We find $S_8D_{IA}=0.8954_{-0.039}^{+0.054}$, where systematics are at the level of roughly 60% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Fracture-based shape optimization built upon the topological derivative

In Silva et al. (2011) and Alidoost et al. (2020), the authors developed an approximation of the energy release rate field associated with a small edge or surface crack at any boundary location and with any orientation using the topological derivative. The approximation is computationally attractive because it requires only a single analysis on the non-cracked domain in contrast with conventional boundary-element and finite-element-based methods, which require a separate and costlier analysis for each crack length-location-orientation combination. Here, a shape optimization scheme for fracture-resistant structures is developed using the energy release rate approximation. In the gradient-based optimization scheme, the domain and its boundary are defined implicitly using level-set functions. The level-set functions of arbitrary geometries are constructed using Boolean operations from the level-set functions of simple primitives. This geometrical representation has the dual advantage of (i) allowing shapes to intersect and/or separate during the optimization and (ii) simplifying the computation of the shape sensitivities.

42 ENGINEERING↗
DOE OSTI2023

Integrating risk assessment methods for carbon storage: A case study for the quest carbon capture and storage facility

This paper documents how tools developed by the National Risk Assessment Partnership (NRAP) complement the Bowtie risk assessment approach through the demonstration of a risk-based Area of Review (AoR) determination for the Quest Carbon Capture and Storage (CCS) facility near Edmonton, Alberta with the NRAP Open-Source Integrated Assessment Model (NRAP Open-IAM). The Bowtie risk assessment for the Quest CCS site was developed by Shell Canada Ltd., who operates the asset on behalf of the Athabasca Oil Sand Project — a joint venture, owned by Canadian Natural Resources Ltd, Chevron Canada and Shell Canada Ltd. The Quest Bowtie treats site risk comprehensively – considering a large set of technical and project risks (e.g., operational risks, above ground infrastructure, public perception, etc.). NRAP tools, methods, and analyses are focused on quantitative assessment of subsurface technical risks. NRAP-Open-IAM was used to evaluate potential groundwater impacts at the Quest site, i.e., a sufficient change above background groundwater quality levels to be measurable, should CO 2 and/or brine leak from the reservoir via a faulty and/or compromised wellbore. Our results show there is a low potential for groundwater impact and support a further reduction (from ~460 to 100 km 2 ) to the established AoR for the Quest site. Integrating both approaches early in the site characterization period could significantly benefit commercial-scale projects by drastically reducing the region over which leakage risks (e.g., legacy wells) need to be evaluated, i.e., the AoR. This is especially true for brownfield sites, which could contain hundreds to thousands of legacy wells. Further, basing monitoring network design on those regions where impacts are most likely to occur has the potential to facilitate more efficient deployment of monitoring technologies and improve the likelihood of detecting a leak should one occur.

58 GEOSCIENCES↗
DOE OSTI2018

Efficient Implementation of NOCI-MP2 Using the Resolution of the Identity Approximation with Application to Charged Dimers and Long C–C Bonds in Ethane Derivatives

An efficient implementation of the perturb-then-diagonalize nonorthogonal configuration interaction method with second-order Møller-Plesset perturbation theory (NOCI-MP2) is introduced. Relative to other low scaling multireference perturbation theories, NOCI-MP2 often requires a much smaller active space because of the use of nonorthogonal reference configurations. Reworking the NOCI-MP2 equations with the resolution of the identity (RI) approximation enables the method to have the same memory requirements and computational scaling as single reference RI-MP2. The working equations are extended to include single substitutions as required when the reference determinants do not satisfy the Hartree-Fock equations. A detailed computational algorithm is presented along with timings to establish the performance of the implementation. NOCI-MP2 is applied to the binding energy and charge resonance energy in dication and monocation π dimers, as well as didiamantane ethane, and hexaphenylethane. A well-defined set of nonorthogonal determinants are obtained using absolutely localized molecular orbitals (ALMOs), as solutions to the self-consistent field for molecular interactions (SCF-MI) equations corresponding to covalent and ionic determinants. Agreement with experimental information where available, and other multireference methods, is satisfactory, with the use of an 0.3 au level shift to guard against large MP2 amplitudes. For didiamantane ethane and hexaphenylethane, large dispersion forces help stabilize the molecules despite the steric repulsion. However, in the case of hexaphenylethane, the energy penalty from the geometric distortion of the fragments critically weakens the bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗
DOE OSTI2016

SU-F-I-47: Optimizing Protocols for Image Quality and Dose in Abdominal CT of Large Patients

Purpose: Newer CT scanners are able to use scout views to adjust mA throughout the scan in order to achieve a given noise level. However, given constraints of radiologist preferences for kVp and rotation time, it may not be possible to achieve an acceptable noise level for large patients. A study was initiated to determine for which patients kVp and/or rotation time should be changed in order to achieve acceptable image quality. Methods: Patient scans were reviewed on two new Emergency Department scanners (Philips iCT) to identify patients over a large range of sizes. These iCTs were set with a limit of 500 mA to safeguard against a failure that might cause a CT scan to be (incorrectly) obtained at too-high mA. Scout views of these scans were assessed for both AP and LAT patient width and AP and LAT standard deviation in an ROI over the liver. Effective diameter and product of the scout standard deviations over the liver were both studied as possible metrics for identifying patients who would need kVp and/or rotation time changed. The mA used for the liver in the CT was compared to these metrics for those patients whose CT scans showed acceptable image quality. Results: Both effective diameter and product of the scout standard deviations over the liver result in similar predictions for which patients will require the kVp and/or rotation time to be changed to achieve an optimal combination of image quality and dose. Conclusion: Two mechanisms for CT technologists to determine based on scout characteristics what kVp, mA limit, and rotation time to use when DoseRight with our physicians’ preferred kVp and rotation time will not yield adequate image quality are described.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
DOE OSTI2018

Voltron Compatible Whole Building Root-Fault Detection and Diagnosis

Buildings consume more than 40% of primary energy in the U.S. Malfunctioning sensors, components, and control systems, as well as degrading components in Heating, Ventilating and Air-conditioning (HVAC) and lighting systems are main reasons for energy waste and unsatisfactory indoor environment. Field studies have shown that an energy saving of 5-30% of total building energy consumption and improved indoor air quality can be achieved by simply applying automated fault detection and diagnosis (AFDD), followed by corrections even if these are not done in real time. Extensive research has been made on the development of component level AFDD tools in the past two decades. However, in recent years, the development of method for a whole building level AFDD has received much attention. Here, a whole building fault refers to a fault happening in one subsystem but impact on more than one subsystems, or has a significant impact on building performances, such as building’s energy consumption. Existing component level AFDD tools could fail to detect or give false alarm for faults that trigger abnormalities in multiple subsystems. Isolating such whole building faults, which have impacts on multiple subsystems, is also challenging by simply using component based AFDD solutions. On the other hand, it might be more cost-effective for medium- or small-sized commercial buildings that have subsystems (e.g. primary cooling subsystem, air loop subsystem, heating subsystem, lighting subsystem, etc.) to install one whole building level AFDD tool, rather than many component level AFDD tools, to focus on significant faults. The focus of this project is firstly to provide training opportunities in building AFDD research area for undergraduate students and to develop a workforce pipeline in building sciences. The objective of the proposed research activities is to develop cost-effective and scalable AFDD solutions for whole building level faults. The developed AFDD solution is VOLTTRONTM compatible to further increase its plug-n-play capacity and the market penetration. VOLTTRONTM is an open-source innovative distributed control and sensing software platform developed by the Pacific Northwest National Laboratory. A VOLTTRONTM compatible AFDD tool brings the benefits such as low-cost deployment, and better building to grid integration, etc. The performance of the developed whole building AFDD tools is evaluated using data collected from a mixed-use medium-sized university campus building. Another significant goal of this project is to engage undergraduate students in research activities and expose them to building control and AFDD fields. A demonstration building – Nesbitt Hall at Drexel University is identified for this study. This demonstration building has a typical HVAC system configuration, which includes a water-cooled chiller system, three variable air volume (VAV) air handling unit (AHU) systems, and a hydronic heating system. Faults, that are expected to have a whole building level impact, are artificially implemented in this demonstration building for three different seasons. Building data have been collected in this project, which include fault free building automation system (BAS) data and BAS data that contain system behaviors caused by artificially implemented and naturally occurred faults. These collected data are used to evaluate the developed whole building AFDD tools. A data-driven method, which includes a weather and schedule-based pattern matching (WPM) method and Feature based Principal Component Analysis (FPCA) method, is developed for whole building level fault detection. Parameter sensitivity tests, including snapshot window size, data sample searching pool size, etc., are implemented to evaluate the impacts of various WPM-FPCA parameters. A data-driven and expert knowledge/rule-based method using Bayesian Network (BN) and WPM is developed for whole building level fault diagnosis. The developed WPM-BN method, which includes a two-layer BN structure model and BN parameters, are either learned from baseline data or developed from expert knowledge. The developed whole building AFDD tools are evaluated using BAS data collected from the demonstration building. Using the evaluation data set, the WPM-FPCA fault detection method is evaluated under two different Principle Component (PC) retention rates, i.e., 0.65 retention rate and 0.95 retention rate. It is observed that when using 0.65 PC retention rate, the WPM-FPCA fault detection method achieves a 79% fault detection rate (this rate reaches to 85% when including the six make-up fault test cases discussed in the next bullet), while when using 0.95 PC retention rate, the WPM-FPCA fault detection method achieves 100% fault detection rate (this rate remains to be 100% when including the six make-up fault test cases). Under both PC retention rates, the WPM-FPCA fault detection method demonstrates 0% false alarm rates. Using the evaluation data set, the developed WPM-BN fault diagnosis method has successfully diagnosed thirteen (13) faults out of the fourteen (14) fault test cases. The one mis-diagnosed case exhibits fewer fault symptoms in different subsystems, when compared with other fault test cases. Overall speaking, the developed whole building AFDD solutions demonstrate satisfactory fault detection/diagnosis accuracy with very low false alarm rate. Lastly, a survey and market study has been performed to understand the existing AFDD market, including its gaps and needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Exploring the Energy Frontier through Precision Tests and Fast Tracking with the CMS Detector (Final Technical Report)

This Early Career Award supported a research program using the CMS experiment at the CERN LHC to probe physics beyond the Standard Model in the top quark and Higgs boson sectors, alongside detector and trigger developments for the High-Luminosity LHC (HL-LHC) upgrade. The program (i) searched for charged lepton flavor violation (LFV) in the top quark sector with the full CMS Run-2 data set, placing the world’s strongest limits to date on the $t → eµq\ (q = u/c)$ branching fraction; (ii) developed preliminary analysis methods toward a boosted $t\bar{t}H(b\bar{b})$ measurement of the top quark Yukawa coupling and its CP properties; (iii) made leading contributions to the hardware-based Level-1 (L1) track finding system for the upgraded CMS detector for HL-LHC; and (iv) developed novel L1 trigger algorithms, notably a displaced vertex trigger enabling new searches for exotic long-lived particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1991

Integration of SAR and DEM data: Geometrical considerations

General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.

Kropatsch, Walter G.↗
NASA NTRS1992

Design and Analysis Techniques for Concurrent Blackboard Systems

Blackboard systems are a natural progression of knowledge-based systems into a more powerful problem solving technique. They provide a way for several highly specialized knowledge sources to cooperate to solve large, complex problems. Blackboard systems incorporate the concepts developed by rule-based and expert systems programmers and include the ability to add conventionally coded knowledge sources. The small and specialized knowledge sources are easier to develop and test, and can be hosted on hardware specifically suited to the task that they are solving. The Formal Model for Blackboard Systems was developed to provide a consistent method for describing a blackboard system. A set of blackboard system design tools has been developed and validated for implementing systems that are expressed using the Formal Model. The tools are used to test and refine a proposed blackboard system design before the design is implemented. My research has shown that the level of independence and specialization of the knowledge sources directly affects the performance of blackboard systems. Using the design, simulation, and analysis tools, I developed a concurrent object-oriented blackboard system that is faster, more efficient, and more powerful than existing systems. The use of the design and analysis tools provided the highly specialized and independent knowledge sources required for my concurrent blackboard system to achieve its design goals.

Mcmanus, John William↗
NASA NTRS1992

Improved HIRAP flight calibration technique

A method of removing non-aerodynamic acceleration signals and calibrating the High Resolution Accelerometer Package (HiRAP) has been developed and improved. Twelve HiRAP mission data sets have been analyzed applying the improved in-flight calibration technique. The application of flight calibration factors to the data sets from these missions produced calibrated acceleration levels within +/- 5.7 micro-g of zero during a time in-flight when the acceleration level was known to be less than 1 g. To validate the current in-flight calibration technique, the atmospheric density results, specifically the normal-to-axial density ratios, have been compared with the analysis results obtained with the previous in-flight calibration technique. This comparison shows an improvement (up to 12.4 percent per flight) in the density ratio when the updated in-flight calibration technique is used.

Moats, Christina D.↗
NASA NTRS1995

Interpretation of Dynamics Explorer far UV images of the quiet time thermosphere

A selected set of far ultra violet images of Earth have been analyzed quanitatively to establish their validity for studying thermospheric weather. The set of images chosen for the study was restricted to mostly geomagnetically quiet conditions in order to obtain a baseline understanding of the relationship between the observations and thermospheric phenomenology. The images included low to modrerate solar activity levels. A new model was developed to generate global dayglow images using first principles methods. The mass Spectrometer/incoherent scatter (MSIS-86) model was used to predict the thermospheric concentrations. The analyses of thermospheric images observed in the 123 to 160-nm nominal passband show that the spectral composition for observations on the projected earth disk is dominated by O I 130.4-nm radiation (85-90%), with concentrations from O I 135.6-nm and N2 Lyman-Birge-Hopefield (LBH) bands of about 5-8% each. The synthetic images reproduce the global features of the observed images rather well. Differences between the model and the data are attributed to real atmospheric effects, such as atomic oxygen depletions which are not well reproduced by the MSIS model when geomagnetic activity is elevated. The absoute values recorded were 38-54% higher than predicted. We attribute this discrepancy to low values of the solar extreme ultraviolet irradiances used in the model. Images obtained in the 136 to 165-nm nominal passband are a factor of 2.7 greater than the model. The excess signal observed is most likely due to a long wavelength tail in the instrument sensitivity which allowed Rayleigh scattered sunlight between 180and 250nm to be detected. The understanding of the Dynamics Explorer (DE 1) images gained by this study provides the basis for future work on the global response of the theremosphere to geomagnetic forcing.

Meier, R. R.↗
NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗
NASA NTRSDate not supplied

HLPW-4/GMGW-3: Overview and Workshop Summary

The Fourth AIAA CFD High Lift Prediction Workshop and the Third Geometry and Mesh Generation Workshop were held collaboratively with the common goal of assessing the numerical prediction capability of current-generation computational fluid dynamics (CFD) technology for swept, medium/high-aspect-ratio wings in high-lift configurations. A key aspect of this joint endeavor was the use of Technology Focus Groups, an innovative new approach for workshops involving close collaboration between participants. These groups, which included both mesh generation and flow solver experts, worked to accelerate advancements for their particular methodologies by addressing key questions of importance {\em prior} to the workshop. The high-lift version of the NASA Common Research Model (CRM-HL) configuration was the focus of this workshop. Measured experimental wind tunnel data were available for comparison. The workshop also included a two-dimensional turbulence model verification exercise based on the CRM-HL wing shape. Altogether, 44 participants submitted a total of 184 data sets of CFD results. This paper provides a high-level summary of the results and conclusions from the workshop. Like at past workshops, fixed-grid Reynolds-averaged Navier-Stokes continued to be inaccurate and inconsistent for high lift. However, mesh adaptation definitively brought more consistency. Scale-resolving methods appeared most promising for predicting high-lift flow physics.

Christopher L Rumsey↗
DOE OSTI2020

Analysis of the Impurity MgOHCl in Molten Chloride Salts Toward its Electrochemical Removal from CSP Plants During Operation

The work presented here is a study of the impurity MgOHCl in molten chloride salts, toward the eventual goal of electrochemically removing it from operational molten-chloride-based concentrating solar power (CSP) plants.1,2 Implementation of molten chloride salts as a heat transfer fluid is among the most promising pathways for decreasing the levelized cost of energy (LCOE) of CSP systems because its high thermal stability allows higher operating temperatures, and thus, greater efficiency. However, this impurity - formed when MgCl2 salts are exposed to air and moisture - cause significant corrosion of containment alloys.1 Therefore, we have developed and validated in a laboratory setting: 1) a method for the formation of MgOHCl for controlled impurity spike in molten salt for its further sensing, evaluation, and reduction; 2) evaluated its diffusion in the molten salt, and 3) began assessing its electrochemical properties. Our findings allow us to propose solutions for efficiently and instantly removing MgOHCl from an operational CSP plant.

concentrated solar power↗