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NASA NTRS2019

InSight's Reconstructed Aerothermal Environments

The InSight Mars Lander successfully landed on the surface on November 26, 2018. This poster will describe the methodologies and margins used in developing the aerothermal environments for design of the thermal protection systems (TPS), as well as a prediction of as-flown environments based on the best estimated trajectory. The InSight mission spacecraft design approach included the effects of radiant heat flux to the aft body from the wake for the first time on a US Mars Mission, due to overwhelming evidence in ground testing for the European ExoMars mission (2009/2010) [1] and 2010 tests in the Electric Arc Shock Tube (EAST) facility [2]. The radiant energy on an aftbody was also recently confirmed via measurement on the Schiaparelli mission [3]. In addition, the InSight mission expected to enter the Mars atmosphere during the dust storm season, so the heatshield TPS was designed to accommodate the extra recession due to the potential dust impact. This poster will compare the predicted aerothermal environments using the reconstructed best estimated trajectory to the design environments. Design Approach: The InSight spacecraft was planned to be a near-design-to-print copy of the Phoenix spacecraft. The determination of the heatshield TPS requirements was approached as if it was a new design due to the new requirement of flying through a dust storm. The baseline for aftbody was build-to-print, and all analyses focused on ensuring adequate margin. This proved to be a challenge because the Phoenix aftbody was designed to withstand only convective heating and the InSight aftbody was evaluated for both convective and radiative heating. Aerothermal environments were predicted using the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and the Data Parallel Line Relaxation (DPLR) CFD codes, and the Nonequilibrium Radiative Transport and Spectra Program (NEQAIR) utilizing bounding design trajectories derived from Monte Carlo analyses from the Program to Optimize Simulated Trajectories II (POST2). In all cases, super-catalytic flowfields were assigned to ensure the most conservative heating results. Two trajectories were evaluated: 1) the trajectory with the maximum heat flux was utilized to determine the flowfield characteristics and the viability of the selection of TPS materials; and 2) the trajectory with the maximum heat load was used to determine the required thicknesses of the TPS materials. Evaluation of the MEDLI data [4], along with ground test data [5] led to the determination of whether or not the flow would transition from laminar to turbulent on the heatshield, which also determined the TPS sizing location for the heatshield. Aerothermal margins were added for the convective heating and developed for the radiative heating. TPS material sizing was determined with the Reaction Kinetic Ablation Program (REKAP) and the Fully Implicit Ablation and Thermal Analysis program (FIAT) using a three-branched approach to account for aerothermal, material response, and material properties uncertainties. In addition, the heatshield recession was augmented by an analysis of the effect of entry through a potential dusty atmosphere using a methodology developed in References [6] and [7]. These analyses resulted in an increase to the Phoenix heatshield TPS thickness. Reconstruction Efforts: Once the best estimated trajectory is reconstructed by the team, the LAURA/HARA (High-Temperature Aerothermo-dynamic Radiation model) and DPLR/NEQAIR code pairs will be used to predict the as-flown aerothermal conditions. In these runs, fully-catalytic flowfields will be assigned because it is a more physically accurate description of the chemistry in the flow. Once again, determination of the onset of turbulence on the heatshield will be evaluated. The as-flown aerothermal environments will then be compared to the design environments.

Beck, R. A.↗

NASA NTRS2019

NuStar Hard X-Ray View of Low-Luminosity Active Galactic Nuclei: High-Energy Cutoff and Truncated Thin Disk

We report the analysis of simultaneous XMM-Newton+Nuclear Spectroscopic Telescope Array (NuSTAR) observations of two low-luminosity active galactic nuclei (LLAGNs), NGC3998 and NGC4579. We do not detect any significant variability in either source over the ∼3 day length of the NuSTAR observations. The broadband 0.5–60 keV spectrum of NGC3998 is best fit with a cutoff power law, while the one for NGC4579 is best fit with a combination of a hot thermal plasma model, a power law, and a blend of Gaussians to fit an Fe complex observed between 6 and 7 keV. Our main spectral results are the following: (1) neither source shows any reflection hump with 3σ reflection fraction upper limits of R < 0.3 and R < 0.18 for NGC3998 and NGC4579, respectively; (2) the 6–7 keV line complex in NGC4579 could be fit with either a narrow Fe K line at 6.4 keV and a moderately broad Fe XXV line or with three relatively narrow lines, which include contribution from Fe XXVI; (3) the NGC4579 flux is 60% brighter than previously detected with XMM-Newton, accompanied by a hardening in the spectrum; (4) we measure a cutoff energy = - E 107+ cut 18 27 keV in NGC3998, which represents the lowest and best constrained high-energy cutoff ever measured for an LLAGN; (5) the NGC3998 spectrum is consistent with a Comptonization model with either a sphere (τ ≈ 3 ± 1) or slab (τ ≈ 1.2 ± 0.6) geometry, corresponding to plasma temperatures between 20 and 150 keV. We discuss these results in the context of hard X-ray emission from bright AGNs, other LLAGNs, and hot accretion flow models.

Younes, George↗

NASA NTRS2015

Risk Informed Philosophy: Using What We Fear to Lose to Guide Us to Success

When an organization sets out on a new effort, program, or project, one of the first steps undertaken is to understand the related requirements. Most often, these requirements come in the form of standards, directives, or other organizational processes, and are derived to meet a broad range of efforts, programs, and projects. The net result is that organizations or teams are forced to start with a maximum set of requirements and expend time and energy tailoring the set of requirements down to what is more appropriate for the effort, program, or project at hand. This presentation will present an alternate method for the application of requirements or best practices that is based upon the actual risks to the safety, performance, or success of the effort. This additive route for applying best practices and requirements also encourages an early exploration of the risks, thus yielding a better understanding of where resources should be applied. This presentation also extends this concept of risk-based application of best practices and requirements to the selection of organization-wide improvement or standardization efforts, such as Lean, Six Sigma, and Quality Management Systems.

Darpel, Scott↗

NASA NTRS2019

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗

NASA NTRS2019

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.

Hylke E. Beck↗

NASA NTRSDate not supplied

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process.

Daniel Bae↗

NASA NTRS2021

NASA High Efficiency, High OPR Capable Small Core Compressor

As future aircraft become lighter and more aerodynamically efficient, thrust requirements will decrease, reducing the core size of the engine. Furthermore, in the pursuit of improved fuel burn, engine overall pressure ratio and bypass ratio will increase, further driving down engine core size (core size being defined as high-pressure compressor [HPC] exit-corrected flow). These drivers together mean that the core size for future single-aisle aircraft applications will shrink below 3.0 lb/s. Traditionally, this small core compressor size is in the domain of axi-centrifugal designs, machines that are typically less efficient and limited to pressure ratios of ~25 due to stress and thermomechanical fatigue in the centrifugal impeller. In this light, NASA and Pratt & Whtiney (P&W) embarked upon a program to develop technologies to enable an all-axial high-pressure compressor with a core size below 3.0 lb/s and an overall pressure ratio greater than 50. The challenge with an all-axial high-pressure compressor at this core size is the small span at the rear of the compressor. As core size is scaled down, the rotor tip clearances, stator hub seal clearances, fillet sizes and leading edge thicknesses do not scale, leading to significant efficiency penalties. The goal of this program is to recover this lapse and realize the cycle benefits of small core size and high overall pressure ratio. The small core challenges described are mitigated through design optimization and technology insertion, enabling an estimated 5 to 10% fuel burn reduction relative to 2020 best-in-class. Three test rigs run at NASA Glenn Research Center evolved the small core design: a low-speed rig to vet technology and validate tools, and two high speeds rigs, the first to demonstrate an optimized meanline design and the second to validate technology to manage large rotor tip gaps. The efficiency improvement validated with these rigs has unlocked the small core design space, demonstrating that small core compressors can maintain a similar efficiency to current best-in-class large core size compressors. In addition to advancing the state-of-the-art of technology, the program has also advanced the modeling standards for multistage compressors with large clearance-to-span ratios. A best practice modeling standard was developed over the course of the program, incorporating learning from all three rig programs.

Axial Compressors↗

NASA NTRSDate not supplied

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Daniel Bae↗

NASA NTRS2021

Supercritical Water Oxidation (SCWO) Trade Study and 2021 Final Report

SCWO is a promising technology whose main benefits is that it is capable of completely mineralizing organic compounds in wastewater and separating inorganic salts. This means that SCWO can theoretically function as a single step water treatment system. It performs the functions of both the primary treatment system and the secondary brine drying function to achieve near 100% water recovery. It can also handle solids so no pretreatment of the feed is required. A preliminary trade study indicates that SCWO could be competitive with the ISS state of the art if its power consumption could be reduced. Thermal and mechanical energy recovery system exist that could reduce SCWO energy consumption to a level that is competitive with the state of the art. In addition, increasing the feed wastewaters organic content by including other wastes, such as feces, could produce a reactor that is thermally self-sustaining. There are 5 different types of SCWO reactors. They are; tubular, tank, impingement, transpiring wall reactors (TWR) and super critical water mixing (SCWM) reactors. Of these the best suited for NASA missions are the impingement and SCWM reactors. The impingement reactor is best suited for near term missions because it can treat the low organic content wastewaters such as are expected for initial Lunar and Mars missions and has the ability to remove precipitated inorganic solids. The SCWM reactor is best suited for longer duration CELSS type missions where high organic content wastewater is available and will resolve solids fouling and corrosion issues. In addition, these two reactors have a long NASA heritage and have been developed specifically for space flight application. Tubular reactors suffer from plugging issues which is a safety concern. Tank reactors will increase in size inversely with gravity, which will trade poorly in Lunar and Mars environments where gravity is reduced. TWR reactors require high organic content wastewater feed and the SCWM reactor is an optimized version of the TWR for NASA applications. It is recommended that in FY 2022 NASA continue to fully evaluate the ability of SCWO to produce potable water and remove inorganics as a solid byproduct. This should be done using the impingement reactor for near term missions and SCWM for longer duration missions. NASA should also develop optimized recuperative heat exchangers and pressure recovery devices to reduce power consumption and investigate inclusion of feces and other organic wastes into the wastewater model to increase its organic content and further reduce thermal energy requirements.

Supercritical Water Oxidation↗

NASA NTRSDate not supplied

Thermodynamic and Diffusion Model Estimates on Metamorphic Temperatures and Timescales for Basaltic Eucrite GRA 98098

Introduction: HED meteorites are thought to rep-resent igneous rocks from Vesta’s basaltic crust and preserve evidence of early crustal metamorphism. Determining the temperatures and timescales of thermal metamorphism is important for reconstructing crustal evolution in the early solar system. Here, we study basaltic eucrite Graves Nunataks (GRA) 98098, which has been identified as a highly metamorphosed eucrite [1]. We present new estimates on metamorphic temperatures determined via thermodynamic modeling as well as the initial results from diffusion models constraining timescales of thermal metamorphism. Sample Description: GRA 98098 is an unbrecciated eucrite with a granoblastic plagioclase and pyroxene mineralogy. Millimeter to cm-long lathes of tridymite cross-cut and poikilitically enclose plagioclase and pyroxene [1,this work]. Pyroxene grains have exsolved into Ca-rich (~Wo38En29Fs33) and Ca-poor (~Wo4.5En36Fs59.5) lamellae. Both unzoned and zoned plagioclase grains are observed. Unzoned plagioclase grains are found solely with tridymite laths. These grains have ~An92 compositions. The cores of the zoned plagioclase grains have the same composition and thin, relatively sodic rims (~An67), (Fig. 1). The bulk sample is unusually enriched in highly in-compatible elements and has one of the most fractionated REE patterns reported [1]. Maximum metamorphic temperatures of 985±78°C have been estimated using two-pyroxene thermometry [2]. Methods: Thermodynamic modeling. Thermodynamic models were constructed using the software Perple_X, which employs a Gibbs free energy minimization in order to determine the most stable phase assemblage for a given bulk rock composition [3]. Bulk composition was calculated using mineral com-positions acquired via EMPA (this study) and the observed abundancies present in the thin section. Two bulk compositions were estimated; 1) includes all phases present in the thin section, (assumes that all phases are present during metamorphism), 2) excludes tridymite from the bulk calculation (assumes that tridymite was not present during metamorphism). In order to determine whether metamorphic equilibria was achieved and estimate temperatures of metamorphism, we compared measured pyroxene compositions with thermodynamically predicted compositions [4, Fig. 2]. Diffusion Modeling. Several time-temperature de-pendent diffusion profiles were calculated in order to determine the best match for XAn chemical profiles observed at the edges of the zoned plagioclase (Fig. 3). We assumed that the start condition was a stepwise gradient at the plagioclase/pyroxene interface. We also assumed an average diffusion coefficient (D) and a constant temperature using the equation in [5]. D was determined for two temperatures (T = 1060ºC; near eucrite solidus [6] and T = 985ºC; metamorphism reported in [4]) and then XAn was calculated as a function of distance from plagioclase core to rim using an error function solution to Fick’s second law. Results: Thermodynamic model results are summarized in Fig. 2. For a bulk composition that includes all phases in the thin section, pyroxene endmember compositions plot in the following temperature ranges: Fs ~660-860ºC, En~1000ºC & 1150ºC, and Wo~760-900ºC (Fig. 2a). For a bulk composition that excludes tridymite from the peak metamorphic assemblage (i.e., the bulk composition minus the contribution from tridymite), a temperature range could not be determined for the Fs component of pyroxene. For Wo, T~760-900ºC and En, T~1000ºC & 1150ºC (Fig. 2b). Fig. 3 summarizes the diffusion model results. For T = 1060°C & 985°C, the most appropriate time interval was estimated based on which diffusion curve most matched (solid lines, Fig. 3) the EMPA data. For T = 1060°C, the best looking match was t = 500 ka. For T = 985°C, the best match was t = 7 Ma. Discussion and future work: Temperature estimates from thermodynamic models are not conclusive because the temperature ranges determined for pyroxene endmember stability do not overlap (colored fields in Fig. 2), thus implying that there is disequilibrium between pyroxene crystals and the bulk composition considered [4]. Thus, additional exploration is needed to define a metamorphically equilibrated do-main that accurately records peak temperature. The utility of defining metamorphically equilibrated do-mains to improve the accuracy and level of detail elucidated regarding the petrogenetic history of metamorphose samples has been demonstrated previously [4,7]. We suggest that in the case of Fig. 2a, the thin section composition is not representative of the length scales over which metamorphic equilibrium was achieve and in the case of Fig. 2b, the assumption that tridymite was not present during metamorphism was incorrect. However, results from thermodynamic models can provide insight into the relative timing of mineral and compositional textures. For example from texture alone, it is unclear whether tridymite was igneous in origin and represents the last bits of melt in a crystallizing magma chamber, or if it formed during (and possibly initiated) open system thermal metamorphism. The latter could be consistent with a partial melt hypothesis [8,9] while the former implies that simple fractional crystallization can yield the textures present in GRA 98098. The lack of coincidence be-tween pyroxene endmember compositions in Fig. 2b suggest that the bulk composition minus tridymite was not the assemblage in equilibrium with the pyroxene, suggesting that tridymite was present during metamorphism and formed during igneous crystallization. We conclude that the development of the Na-rich plagioclase rims likely occurred during or immediately after peak thermal metamorphism, because eucrites of similar metamorphic grade and texture have unzoned plagioclase (~An92) [2,4,8], and Na zoning is only observed in the plagioclase not included in the tridymite. This suggests that the zoning formed after tridymite formation, and therefore after igneous crystallization. Thus, the timescales calculated via diffusion modeling possibly represent the time interval over which thermal metamorphism occurred. Cooling rates approximated for the Vestan crust predict that the crust cooled below 300°C around 35-40 Ma after formation[10]. This is consistent with our modeling results that predict formation of the Na rich plagioclase rims occurring at higher temperatures over a period of 0.5 to 7 Ma years. Future work. Additional thermodynamic modeling work will focus on selecting an equilibrated bulk rock domain in which to elucidate metamorphic conditions. Diffusion models currently provide a minimum time-scale, since diffusion slows down as the system cools. Future work with will focus on integrating cooling into the diffusion models and constraining the depth at which thermal metamorphism occurs because it could be used to determine whether the range of time-scales calculated for thermal metamorphism are consistent with the geologic environment.

J S Gorce↗

NASA NTRS2022

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗

NASA NTRS2021

Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction with Satellite Data for Rural Areas

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS-Chem, WRF-Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non rural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two-part study develops a multimodel and multi-AOD bias-correction technique that has the potential to improve PM2.5 forecasts in both rural and non rural areas in near real time, and be readily implemented at state levels.

Huanxin Zhang↗

NASA NTRS2023

A New Model of Dry Firn Densification Constrained By Continuous Strain Measurements Near South Pole

Converting measurements of ice-sheet surface elevation change to mass change requires measurements of accumulation and knowledge of the evolution of the density profile in the firn. Most firn-densification models are tuned using measured depth-density profiles, a method which is based on an assumption that the density profile in the firn is invariant through time. Here we present continuous measurements of firn-compaction rates in 12 boreholes near the South Pole over a two-year period. To our knowledge, these are the first continuous measurements of firn compaction on the Antarctic Plateau. We use the data to derive a new firn-densification algorithm framed as a constitutive relationship. We also compare our measurements to compaction rates predicted by several existing firn densification models. Results indicate that an activation energy of 60 kJ mol (−1), a value within the range used by current models, best predicts the seasonal cycle in compaction rates on the Antarctic Plateau. Our results suggest models can predict firn-compaction rates with at best 7% uncertainty and cumulative firn compaction on a two year timescale with at best 8% uncertainty.

C. Max Stevens↗

DOE OSTI2020

FEMP Facility Evaluation (Audit) Decision Tree

This document is a resource to be used in concert with FEMP Audit Definitions, FEMP Consolidated Facility Management Guidance, and agency best practices and expert judgment—for agencies to use to determine the best approaches to evaluate their facilities. It features a decision tree that provides a framework for agencies to interpret gathered facility data to understand the existing conditions; benchmark the facility against others in the portfolio to determine whether an on-site or remote audit is appropriate for a facility; determine the best remote or on-site audit level of detail to meet agency facility auditing goals, such as meeting Energy Independence and Security Act of 2007 requirements and developing projects; and improve their energy and water management programs.

auditing↗

DOE OSTI2020

Studies on the Encapsulation of Brine Generated from a Process Using Selective Electrodialysis Reversal

This topical report summarizes the laboratory testing, geochemical modeling, and mineralogical testing conducted to examine the efficacy of wastewater encapsulation for the brine generated from the Saltworks Flex electrodialysis reversal technology. Within the laboratory testing, the short- and long-term physical properties of seven separate mix designs were examined along with the leaching of each mix design. Additionally, geochemical thermodynamic modeling was used along with mineralogical analyses to help gain a fundamental understanding of the chemistry involved in the encapsulation process. Encapsulation is a process that results in the immobilization of constituents of interest by creating an engineered material that contains the waste within its matrix, both physically and chemically, in such a manner that the receiving environment is protected from adverse effects. Within the context of this study, encapsulation mix designs involved mixing the Saltworks brine with fly ash and various additives, principally lime (calcium oxide) and cement, to form a paste that eventually sets and hardens into a monolith upon placement in a landfill. Moisture conditioning fly ash with wastewater sources for on-site landfill disposal is a process that is in use at some sites and has been presented as a viable option to dispose of liquid wastes. However, because chemical reactions that can lead to sequestration of constituents of interest are not optimized, leaching can occur. Therefore, in this study, mixes were created to mimic moisture conditioning, as well as engineered pastes of varying mix designs. The study found that engineered encapsulation mixes provide significant resistance to leaching compared to moisture conditioning alone. The best performing encapsulation mix used lime as the additive, which proved superior to the use of cement. After 90 days of curing, this encapsulated mix was 5.5 times stronger than the moisture conditioned mix. Additionally, this mix exhibited an approximate 2.5 order of magnitude drop in hydraulic conductivity compared to the moisture conditioned mix. When comparing leaching, nearly all the chloride was found to evolve from the moisture conditioned mix, whereas only 6.7% of the chlorine contained in the best performing encapsulated mix leached out. Mineralogical analysis via X-ray diffraction (XRD) showed a significant concentration of the chloride sequestering mineral, Friedel’s salt, in the best performing encapsulation mix, whereas none was observed in the moisture conditioned mix, pointing to it being the primary chemical mechanism for chloride retention, along with the physical impermeability of the material. With respect to the modeling study, the model was successful in predicting the presence of most mineral phases observed in the XRD analysis.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Impact of Hybrid Energy Storage System (HESS) Topologies on Performance: Exploration for Hydropower Hybrids

We investigate the technical performance of six HESS topologies integrated with run-of-river (ROR) hydropower to provide frequency support. We choose ROR hydropower because there are 23 GW of installed ROR hydropower in the U.S. and integrating these plants with energy storage could boost their contribution to grid services. We focus on HESSs composed of batteries and ultracapacitors because batteries are cost effective for storing energy but degrade more quickly as a function of cycling. In contrast, ultracapacitors can be cycled millions of times and are cost effective for quick injections of power. We find that active HESS topologies demonstrate the best overall improvement to grid frequency during a contingency while adhering to the power ramping limits of the HESS devices. Future work will investigate other services to identify if one HESS topology performs best for all services of interest or, more likely, different HESS topologies are best suited for specific services.

13 HYDRO ENERGY↗

DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗

DOE OSTI2020

Parallel Particle Advection Bake-Off for Scientific Visualization Workloads

There are multiple algorithms for parallelizing particle advection for scientific visualization workloads. While many previous studies have contributed to the understanding of individual algorithms, our study aims to provide a holistic understanding of how algorithms perform relative to each other on various workloads. To accomplish this, we consider four popular parallelization algorithms and run a “bake-off” study (i.e., an empirical study) to identify the best matches for each. The study includes 216 tests, going to a concurrency of up to 8192 cores and considering data sets as large as 34 billion cells with 300 million particles. Overall, our study informs three important research questions: (1) which parallelization algorithms perform best for a given workload?, (2) why?, and (3) what are the unsolved problems in parallel particle advection? In terms of findings, we find that the seeding box is the most important factor in choosing the best algorithm, and also that there is a significant opportunity for improvement in execution time, scalability, and efficiency.

Pugmire, Dave↗