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At least 217 records · Page 12

Multilevel Techniques for Compression and Reduction of Scientific Data---The Multivariate Case

We develop a technique for multigrid adaptive reduction of data (MGARD). Special attention is given to the case of tensor product grids, where our approach permits the use of nonuniformly spaced grids in each direction, which can prove problematic for many types of data reduction methods. An important feature of our approach is the provision of guaranteed, computable bounds on the loss incurred by the reduction of the data. Many users are leery of lossy algorithms and will only consider using them provided that numerical bounds on the pointwise difference between the original and the reduced datasets are given. Accordingly, we develop techniques for bounding the loss measured in the $L^{\infty}(\Omega)$ norm, and we show that these bounds are realistic in the sense that they do not significantly overestimate the actual loss. Here, the resulting loss indicators are used to guide the adaptive reduction of the data so that the reduced dataset meets a user-prescribed tolerance or memory constraint. Illustrative numerical examples, including the reduction of data arising from the simulation of a nonlinear reaction-diffusion problem, a turbulent channel flow, and a climate simulation, are provided.

97 MATHEMATICS AND COMPUTING↗

Air Leakage and Air Transfer Between Garage and Living Space

This research project focused on evaluation of air transfer between the garage and living space in a single-family detached home constructed by a production homebuilder in compliance with the 2009 International Residential Code and the 2009 International Energy Conservation Code. The project gathered important information about the performance of whole-building ventilation systems and garage ventilation systems as they relate to minimizing flow of contaminated air from garage to living space. Important gaps and barriers addressed by this research were: (1) Developing recommendations for effective methods for precluding the flow of contaminated air from garages to living space. (2) Creating a resource for guiding home builders and retrofitters to achieve garage isolation by use of mechanical ventilation equipment. (3) Providing field measurement support for revision of the EPA Indoor airPLUS program requirements, which are part of the DOE Challenge Home program. Field test data provided in the form of technical report showing blower door test results for air leakage measurements and tracer gas testing results. Waldorf, MD 20602

Array↗

NASA Orbital Debris Engineering Model ORDEM 3.1 - Software User Guide

This National Aeronautics and Space Administration (NASA) Orbital Debris Engineering Model (ORDEM) 3.1 Software User Guide accompanies delivery of the latest upgraded version of the model, ORDEM 3.1. The user guide also provides a top-level program description and a list of capabilities. It includes descriptions of runtime error and information codes, input/output file formats, runtimes for different orbit configurations, and how to use uncertainty files. ORDEM 3.1 supersedes the previous NASA Orbital Debris Program Office (ODPO) models – ORDEM 3.0 (Stansbery, et al. 2014) and ORDEM2000 (Liou, et al. 2002). The availability of new sensor and in situ data, re-analysis of older data, and development of new analytical techniques has enabled the construction of this more comprehensive and sophisticated model. An upgraded graphical user interface (GUI) is integrated with the software. This upgraded GUI uses project-oriented organization and provides the user with graphical representations of numerous output data products. For example, these range from the conventional flux vs. average debris size (or altitude bin) for chosen analysis orbits (or views) to the more complex color-contoured, two-dimensional (2-D) directional flux diagrams in local spacecraft elevation and azimuth. The current model, ORDEM 3.1, supports spacecraft as well as telescope/radar project assessments. ORDEM 3.1 contains updated debris populations covering low Earth orbit (LEO, up to 2000 km altitude) to geosynchronous orbit (GEO, up to 40,000 km altitude) and can assess debris calculations up to year 2050, extending coverage past the previous limit of 2035 in ORDEM 3.0. Although populations differ from its predecessor, ORDEM 3.1 is functionally the same as ORDEM 3.0 and can support ORDEM 3.0 projects through backward compatibility.

Vavrin, Andrew B.↗

NASA Orbital Debris Engineering Model ORDEM 3.2 – Software User Guide

This National Aeronautics and Space Administration (NASA) Orbital Debris Engineering Model (ORDEM) 3.2 Software User Guide accompanies delivery of the latest upgraded version of the model, ORDEM 3.2. The user guide also provides a top-level program description and a list of capabilities. It includes descriptions of runtime error and information codes, input/output file formats, runtimes for different orbit configurations, and how to use uncertainty files. ORDEM 3.2 supersedes the previous NASA Orbital Debris Program Office (ODPO) models – ORDEM 3.0 (Stansbery, et al. 2014) and ORDEM2000 (Liou, et al. 2002). The availability of new sensor and in situ data, re-analysis of older data, and development of new analytical techniques has enabled the construction of this more comprehensive and sophisticated model. An upgraded graphical user interface (GUI) is integrated with the software. This upgraded GUI uses project-oriented organization and provides the user with graphical representations of numerous output data products. For example, these range from the conventional flux vs. average debris size (or altitude bin) for chosen analysis orbits (or views) to the more complex color-contoured, two-dimensional (2-D) directional flux diagrams in local spacecraft elevation and azimuth. The current model, ORDEM 3.2, supports spacecraft as well as telescope/radar project assessments. ORDEM 3.2 contains updated debris populations covering low Earth orbit (LEO, up to 2000 km altitude) to geosynchronous orbit (GEO, up to 40,000 km altitude) and can assess debris calculations up to year 2050, extending coverage past the previous limit of 2035 in ORDEM 3.0. Although populations differ from its predecessor, ORDEM 3.2 is functionally the same as ORDEM 3.0 and can support ORDEM 3.0 projects through backward compatibility.

Andrew Vavrin↗

Barrier elision for production parallel programs

Large scientific code bases are often composed of several layers of runtime libraries, implemented in multiple programming languages. In such situation, programmers often choose conservative synchronization patterns leading to suboptimal performance. In this paper, we present context-sensitive dynamic optimizations that elide barriers redundant during the program execution. In our technique, we perform data race detection alongside the program to identify redundant barriers in their calling contexts; after an initial learning, we start eliding all future instances of barriers occurring in the same calling context. We present an automatic on-the-fly optimization and a multi-pass guided optimization. We apply our techniques to NWChem - a 6 million line computational chemistry code written in C/C++/Fortran that uses several runtime libraries such as Global Arrays, ComEx, DMAPP, and MPI. Our technique elides a surprisingly high fraction of barriers (as many as 63%) in production runs. This redundancy elimination translates to application speedups as high as 14% on 2048 cores. Our techniques also provided valuable insight about the application behavior, later used by NWChem developers. Overall, we demonstrate the value of holistic context-sensitive analyses that consider the domain science in conjunction with the associated runtime software stack.

97 MATHEMATICS AND COMPUTING↗

Advancing User Supports with a Structured How-To Knowledge Base for Earth Science Data

It is a challenge to access and process fast growing Earth science data from satellites and numerical models, which may be archived in very different data format and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and/or formats. A type of structured online document, data recipe, were created in beginning 2013 by Goddard Earth Science Data and Information Services Center (GES DISC). A data recipe is the How-To document created by using the fixed template, containing step-by-step instructions with screenshots and examples of accessing and working with real data. The recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant to some recipes. In 2014, the NASA Earth Science Data System Working Group (ESDSWG) for data recipes was established, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group started with inventory and analysis of existing EOSDIS-wide online help documents, and provided recommendations and guidelines and for writing and grouping data recipes. This presentation will overview activities of creating How-To documents at GES DISC and ESDSWG. We encourage feedback and contribution from users for improving the data How-To knowledge base.

how-to↗

Applications of a damage tolerance analysis methodology in aircraft design and production

Objectives of customer mandated aircraft structural integrity initiatives in design are to guide material selection, to incorporate fracture resistant concepts in the design, to utilize damage tolerance based allowables and planned inspection procedures necessary to enhance the safety and reliability of manned flight vehicles. However, validated fracture analysis tools for composite structures are needed to accomplish these objectives in a timely and economical manner. This paper briefly describes the development, validation, and application of a damage tolerance methodology for composite airframe structures. A closed-form analysis code, entitled SUBLAM was developed to predict the critical biaxial strain state necessary to cause sublaminate buckling-induced delamination extension in an impact damaged composite laminate. An embedded elliptical delamination separating a thin sublaminate from a thick parent laminate is modelled. Predicted failure strains were correlated against a variety of experimental data that included results from compression after impact coupon and element tests. An integrated analysis package was developed to predict damage tolerance based margin-of-safety (MS) using NASTRAN generated loads and element information. Damage tolerance aspects of new concepts are quickly and cost-effectively determined without the need for excessive testing.

Woodward, M. R.↗

A Chemoselective and Stereodivergent Platform of Heme‐Nitrene Transferases to Access Chiral Aryl‐β‐Amino Esters and An Investigation of the Sequence‐Activity Landscape

Engineered biocatalysts can utilize nitrene precursors to access enantioenriched amination products, yet they have not been applied to produce valuable, enantiomerically enriched noncanonical β-amino esters. Current approaches to synthesizing β-amino acids rely on pre-oxidized precursors and multistep synthetic approaches involving various protecting groups. We engineered a platform of heme enzymes for stereoselective C–H bond amination of readily available carboxylic ester derivatives to install primary amines. A directed evolution campaign coupled with sequencing of over 1000 variants enabled us to develop engineered variants that use either O-pivaloylhydroxylamine triflic acid (PONT) or hydroxylamine hydrochloride (H 2 NOH∙HCl) as aminating reagents. An analysis of the resulting sequence–activity dataset revealed additional improvements that could be made to the final variant, highlighting the utility of sequencing data to guide future steps in directed evolution campaigns. Furthermore, the evolved nitrene transferases expand the scope of accessible chiral β-amino acid building blocks for peptidomimetic applications and provide new starting points for the design and synthesis of enantioenriched β-amino acid motifs.

amino ester building blocks↗

Advanced Subsonic Combustion Rig

Researchers from the NASA Lewis Research Center have obtained the first combustion/emissions data under extreme future engine operating conditions. In Lewis' new world-class 60-atm combustor research facility--the Advanced Subsonic Combustion Rig (ASCR)--a flametube was used to conduct combustion experiments in environments as extreme as 900 psia and 3400 F. The greatest challenge for combustion researchers is the uncertainty of the effects of pressure on the formation of nitrogen oxides (NOx). Consequently, U.S. engine manufacturers are using these data to guide their future combustor designs. The flametube's metal housing has an inside diameter of 12 in. and a length of 10.5 in. The flametube can be used with a variety of different flow paths. Each flow path is lined with a high-temperature, castable refractory material (alumina) to minimize heat loss. Upstream of the flametube is the injector section, which has an inside diameter of 13 in. and a length of 0.5-in. It was designed to provide for quick changeovers. This flametube is being used to provide all U.S. engine manufacturers early assessments of advanced combustion concepts at full power conditions prior to engine production. To date, seven concepts from engine manufacturers have been evaluated and improved. This collaborated development can potentially give U.S. engine manufacturers the competitive advantage of being first in the market with advanced low-emission technologies.

Lee, Chi-Ming↗

Stationary Liquid Fuel Fast Reactor

For effective burning of hazardous transuranic (TRU) elements of used nuclear fuel, a transformational advanced reactor concept named SLFFR (Stationary Liquid Fuel Fast Reactor) was proposed based on stationary molten metallic fuel. The fuel enters the reactor vessel in a solid form, and then it is heated to molten temperature in a small melting heater. The fuel is contained within a closed, thick container with penetrating coolant channels, and thus it is not mixed with coolant nor flow through the primary heat transfer circuit. The makeup fuel is semi- continuously added to the system, and thus a very small excess reactivity is required. Gaseous fission products are also removed continuously, and a fraction of the fuel is periodically drawn off from the fuel container to a processing facility where non-gaseous mixed fission products and other impurities are removed and then the cleaned fuel is recycled into the fuel container. A reference core design and a preliminary plant system design of a 1000 MWt TRU- burning SLFFR concept were developed using TRU-Ce-Co fuel, Ta-10W fuel container, and sodium coolant. Conservative design approaches were adopted to stay within the current material performance database. Detailed neutronics and thermal-fluidic analyses were performed to develop a reference core design. Region-dependent 33-group cross sections were generated based on the ENDF/B-VII.0 data using the MC2-3 code. Core and fuel cycle analyses were performed in theta-r-z geometries using the DIF3D and REBUS-3 codes. Reactivity coefficients and kinetics parameters were calculated using the VARI3D perturbation theory code. Thermo-fluidic analyses were performed using the ANSYS FLUENT computational fluid dynamics (CFD) code. Figure 0.1 shows a schematic radial layout of the reference 1000 MWt SLFFR core, and Table 0.1 summarizes the main design parameters of SLFFR-1000 loop plant. The fuel container is a 2.5 cm thick cylinder with an inner radius of 87.5 cm. The fuel container is penetrated by twelve hexagonal control assembly (CA) guide tubes, each of which has 3.0 mm thickness and 69.4 mm flat-to-flat outer distance. The distance between two neighboring CA guide tube is selected to be 26 cm to provide an adequate space for CA driving systems. The fuel container has 18181 penetrating coolant tubes of 6.0 mm inner diameter and 2.0 mm thickness. The coolant tubes are arranged in a triangular lattice with a lattice pitch of 1.21 cm. The fuel, structure, and coolant volume fractions inside the fuel container are 0.386, 0.383, and 0.231, respectively. Separate steel reflectors and B4C shields are used outside of the fuel container. Six gas expansion modules (GEMs) of 5.0 cm thickness are introduced in the radial reflector region. Between the radial reflector and the fuel container is a 2.5 cm sodium gap. The TRU inventory at the beginning of equilibrium cycle (BOEC) is 5081 kg, whereas the TRU inventory at the beginning of life (BOL) was 3541 kg. This is because the equilibrium cycle fuel contains a significantly smaller fissile fraction than the LWR TRU feed. The fuel inventory at BOEC is composed of 34.0 a/o TRU, 41.4 a/o Ce, 23.6 a/o Co, and 1.03 a/o solid fission products. Since uranium-free fuel is used, a theoretical maximum TRU consumption rate of 1.011 kg/day is achieved. The semi-continuous fuel cycle based on the 300-batch, 1- day cycle approximation yields a burnup reactivity loss of 26 pcm/day, and requires a daily reprocessing of 32.5 kg of SLFFR fuel. This yields a daily TRU charge rate of 17.45 kg, including a makeup TRU feed of 1.011 kg recovered from the LWR used fuel. The charged TRU-Ce-Co fuel is composed of 34.4 a/o TRU, 40.6 a/o Ce, and 25.0 a/o Co.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling, Performance Assessment, and Nodal Data Analysis of TRISO-Fueled Systems with Shift

This technical report documents several enhancements to the Shift Monte Carlo (MC) code under the US Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in fiscal year (FY) 2022. Performance enhancements were added to Shift specifically for tristructural isotropic (TRISO)–fueled reactor systems and guided based on performance analysis in FY 2021. For the pebble performance model developed in previous studies, the runtime improved by ~ 91× compared to the original model and ~ 2× compared to the user-optimized model. Compared to Serpent, Shift is ~ 3× slower if Serpent delta-tracking is enabled but ~ 2× faster when delta-tracking is disabled. The multigroup cross section generation was improved through simplifying tally input definitions, porting several post-processing tally operations from Python scripts into the Shift code base, and accounting for production reactions in the scattering multiplicity. Progress was also made on two emerging capabilities: (1) the development of Titan (a Shift reactor physics user interface) and (2) initial investigation into path-length tallies for computing multigroup scattering matrices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗

Python ARM Radar Toolkit (Py-ART) Roadmap

Radar software is key for producing scientific insight from radar data. There are several platforms for interacting with radar data; the open-source variants are well documented in Heistermann et al. 2014. The Python ARM Radar Toolkit (Py-ART; Helmus and Collis, 2016) is one of these. This document is a guiding roadmap for development for Py-ART. It sets priorities for U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility-funded work and it advises the community which contributions are desired and will receive the most assistance from ARM-funded software engineers.

Python ARM Radar Toolkit, linear programming, valu↗

User Guide for TROPICS Data Products

This document provides information for using the data products available from the “Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats” (TROPICS) mission. The TROPICS mission will produce a range of data products that will be available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The data products will be produced at the TROPICS Data Processing Center (UW-M SSEC), and consist of Level-1 radiances (antenna and brightness temperatures), Level-2a unified resolution radiance, Level-2b Atmospheric Vertical Temperature Profiles (AVTP), Level-2b Atmospheric Vertical Moisture Profiles (AVMP), Level-2b Instantaneous Surface Rain Rate (ISRR), and Level-2b Tropical Cyclone (TC) intensity algorithms to estimate two primary variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). Two independent intensity estimation methods are included: 1) the Tropical Cyclone Intensity Estimate algorithm (TCIE) developed at the University of Wisconsin/CIMSS using native microwave brightness temperatures and 2) the Hurricane Intensity and Structure Algorithm (HISA) developed at Colorado State University/CIRA using microwave retrievals of temperature, moisture, and integrated quantities. In addition to MSW and MSLP, HISA also provides estimates of surface wind radii and 2D winds at standard pressure levels. TROPICS is adapting the NOAA STAR Microwave Integrated Retrieval System (MIRS) to retrieve the AVTP and AVMP data products. The ISRR algorithm uses the NASA Goddard Precipitation Retrieval and Profiling Scheme (PRPS).

TROPICS↗

Unalakleet Climate: Analyzing Permafrost Degradation and Drainage Networks in Unalakleet, Alaska

The coastal community of Unalakleet is currently the 8th most at-risk community in Alaska due to the adverse effects of climate change that include permafrost degradation, severe coastal erosion, and sea-level rise-induced flood inundation caused by increasingly frequent storm surges. In response, the community has started a managed relocation with support from the Native Village of Unalakleet (NVU) and the National Renewable Energy Lab (NREL)’s Alaska campus in Fairbanks. The Unalakleet Climate NASA DEVELOP team partnered with NREL to provide remote sensing support and analysis for resilience planning in Unalakleet, supporting their ongoing relocation efforts and guiding future expansion. The team utilized Sentinel-1 C-Synthetic Aperture Radar (SAR), WorldView-2, and WorldView-3 datasets from 2017 – 2023 to analyze seasonal summer subsidence and utilized a 2014 Ancillary USGS 5 m Alaska DEM to conduct drainage network analyses that included watershed delineation and Height Above Nearest Drainage (HAND) analysis. The team also used high-resolution WorldView images to locate stable reference points that served as quality control for the team’s analyses. The team’s end products included maps containing subsidence and drainage zones information at and surrounding the relocation site. The team’s products provide NREL with valuable data that enables them to better assist Unalakleet’s managed relocation and assists Unalakleet with adapting to the catastrophic effects of climate change and build resilience in a community on the front lines of climate change.

Ian Lee↗

Basin-Scale Relicensing Opportunity Product User Guide

The Basin-Scale Relicensing Opportunity products provide a platform for identifying favorable areas for basin-wide collaboration using metrics derived from anticipated Federal Energy Regulatory Commission (FERC) relicensing dates. The hydropower relicensing process requires long-term resource allocation by agencies, hydropower owner/operators, non-governmental organizations, and tribal, state, and federal governments. Basin-scale hydropower relicensing has begun to receive attention as a potential solution for reducing licensing timelines, costs, and uncertainty which can provide benefits to a broad spectrum of participants in the licensing process. Two products were developed: (1) an interactive web map that allows users to browse facilities and rivers of interest and uncover locations for potential collaboration based on FERC relicensing metrics summarized along river reaches and (2) a spreadsheet that contains 1,261 facilities with associated FERC relicensing metrics and that allows users to join these data to others and develop and conduct their own analyses.

13 HYDRO ENERGY↗

Life-cycle analysis of greenhouse gas emissions from hydrogen delivery: A cost-guided analysis

The cost of hydrogen delivery for transportation accounts for most of the current H 2 selling price; delivery also requires substantial amounts of energy. In this work, we developed harmonized techno-economic and life-cycle emissions models of current and future H 2 production and delivery pathways. Our techno-economic analysis of dispensed H 2 costs guided our selection of pathways for the life-cycle analysis. In this paper, we present the results of market expansion scenarios using existing capabilities (for example, those that use H 2 from steam methane reforming, chlor-alkali, and natural gas liquid cracker plants), as well as results for future electrolysis plants that use nuclear, solar, and hydroelectric power. Reductions in greenhouse gas emissions for fuel cell electric vehicles compared to conventional gasoline pathways vary from 40% reduction for fossil-derived H 2 to 20-fold for clean H 2 . Supplemental tables with greenhouse gas emissions data for each step in the H 2 pathways enable readers to evaluate additional scenarios.

08 HYDROGEN↗

A Multi-scale, Geo-data Science Method for Assessing Unconventional Critical Mineral Resources

Critical minerals (CM) supply raw materials that constitute many of our essential infrastructure, defense, technology, and electrification needs. Currently, production and refinement of these materials from conventional sources is limited to few regions globally, which makes supply of these resources particularly venerable to disruption. To help overcome these risks and meet growing demand, attention has focused on identifying and developing resource potential of unconventional geologic CM sources, such as rare-earth elements in sedimentary systems. However, the unconventional nature of these types of sources means they are often poorly characterized and/or under-explored with respect to conventional counterparts. We present a regional case study for an Unconventional Rare-earth and Critical minerals (URC) assessment method for predicting and identifying REE resource potential and occurrence in unconventional systems in the Central Appalachian Basin (CAB). The method utilizes a geologic and geospatial data-driven approach, informed and guided by knowledge of REE enrichment processes, to systematically predict and identify areas of higher enrichment. Results from the test case indicate locations with potential for different types of coal-REE deposits, demonstrating its utility for reducing the area of exploration and identifying sites for more detailed investigation. Building upon the regional scale assessment capability, ongoing science-based enhancements to the method will allow for finer-scale (e.g., mine-scale) predictions required to support technical and economic assessments.

Creason, Christopher↗