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At least 37 records · Page 2

A Proposed Strategy for the U.S. to Develop and Maintain a Mainstream Capability Suite ("Warehouse") for Automated/Autonomous Rendezvous and Docking in Low Earth Orbit and Beyond

The ability of space assets to rendezvous and dock/capture/berth is a fundamental enabler for numerous classes of NASA fs missions, and is therefore an essential capability for the future of NASA. Mission classes include: ISS crew rotation, crewed exploration beyond low-Earth-orbit (LEO), on-orbit assembly, ISS cargo supply, crewed satellite servicing, robotic satellite servicing / debris mitigation, robotic sample return, and robotic small body (e.g. near-Earth object, NEO) proximity operations. For a variety of reasons to be described, NASA programs requiring Automated/Autonomous Rendezvous and Docking/Capture/Berthing (AR&D) capabilities are currently spending an order-of-magnitude more than necessary and taking twice as long as necessary to achieve their AR&D capability, "reinventing the wheel" for each program, and have fallen behind all of our foreign counterparts in AR&D technology (especially autonomy) in the process. To ensure future missions' reliability and crew safety (when applicable), to achieve the noted cost and schedule savings by eliminate costs of continually "reinventing the wheel ", the NASA AR&D Community of Practice (CoP) recommends NASA develop an AR&D Warehouse, detailed herein, which does not exist today. The term "warehouse" is used herein to refer to a toolbox or capability suite that has pre-integrated selectable supply-chain hardware and reusable software components that are considered ready-to-fly, low-risk, reliable, versatile, scalable, cost-effective, architecture and destination independent, that can be confidently utilized operationally on human spaceflight and robotic vehicles over a variety of mission classes and design reference missions, especially beyond LEO. The CoP also believes that it is imperative that NASA coordinate and integrate all current and proposed technology development activities into a cohesive cross-Agency strategy to produce and utilize this AR&D warehouse. An initial estimate indicates that if NASA strategically coordinates the development of a robust AR&D capability across the Agency, the cost of implementing AR&D on a spacecraft could be reduced from roughly $70M per mission to as low as $7M per mission, and the associated development time could be reduced from 4 years to 2 years, after the warehouse is completely developed. Table 1 shows the clear long-term benefits to the Agency in term of costs and schedules for various missions. (The methods used to arrive at the Table 1 numbers is presented in Appendices A and B.)

Krishnakumar, Kalmanje S.↗

A Hydropower Biological Evaluation Toolset (HBET) for Characterizing Hydraulic Conditions and Impacts of Hydro-Structures on Fish

Currently, approximately 16% of the world’s electricity and over 80% of the world’s renewable electricity is generated from hydropower resources, and there is potential for development of a significant amount of new hydropower capacity. However, in practice, realizing all the potential hydropower resource is limited by various factors, including environmental effects and related mitigation requirements. That is why hydropower regulatory requirements frequently call for targets to be met regarding fish injury and mortality rates. Hydropower Biological Evaluation Toolset (HBET), an integrated suite of software tools, is designed to characterize hydraulic conditions of hydropower structures and provide quantitative estimates of fish injury and mortality rates due to various physical stressors including strike, pressure, and shear. HBET enables users to design new studies, analyze data, perform statistical analyses, and evaluate biological responses. In this paper, we discuss the features of the HBET software and describe a case study that illustrates its functionalities. Here, HBET can be used by turbine manufacturers, hydropower operators, and regulators to design and operate hydropower systems that minimize ecological impacts in a cost-effective manner.

13 HYDRO ENERGY↗

Field testing and validation of a low-cost MPC for demand flexibility for grid-interactive K-12 schools

K-12 school buildings account for the highest energy consumption within the public sector. Implementing advanced HVAC controls in grid-interactive K-12 schools could bring substantial economic advantages and grid flexibility. Our previous study demonstrated that a low-cost model predictive control (MPC) solution, which coordinates multiple packaged units, can enable demand flexibility without major hardware upgrades. However, a significant gap remains between academic pilots and market-ready scalable solutions. This paper extends the previous single-site pilot to a multi-site demonstration involving three school campuses (95 total units) through a commercial technology transfer process. Addressing the challenge of verifying performance with sparse field data, we present a new statistical approach using Bayesian methods to estimate the MPC’s effect on peak demand. Unlike traditional methods, this approach robustly quantifies uncertainty in non-normal, limited datasets. The results confirm the solution’s replicability, achieving a 21.6–38.9% reduction in HVAC peak demand (10.8–22.1% at the site-level) with > 98% probability across diverse locations. Finally, we document critical barriers to scaling software-as-a-service (SaaS) solutions–such as API instability and diverse legacy systems–and offer practical strategies to accelerate the commercial adoption of grid-interactive efficient buildings.

Ham, Sang Woo↗

Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors’ impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor's influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20%25 in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Software forecasting as it is really done: A study of JPL software engineers

This paper presents a summary of the results to date of a Jet Propulsion Laboratory internally funded research task to study the costing process and parameters used by internally recognized software cost estimating experts. Protocol Analysis and Markov process modeling were used to capture software engineer's forecasting mental models. While there is significant variation between the mental models that were studied, it was nevertheless possible to identify a core set of cost forecasting activities, and it was also found that the mental models cluster around three forecasting techniques. Further partitioning of the mental models revealed clustering of activities, that is very suggestive of a forecasting lifecycle. The different forecasting methods identified were based on the use of multiple-decomposition steps or multiple forecasting steps. The multiple forecasting steps involved either forecasting software size or an additional effort forecast. Virtually no subject used risk reduction steps in combination. The results of the analysis include: the identification of a core set of well defined costing activities, a proposed software forecasting life cycle, and the identification of several basic software forecasting mental models. The paper concludes with a discussion of the implications of the results for current individual and institutional practices.

Griesel, Martha Ann↗

SolarAPP+ Pilot Analysis: Performance and Impact of Instant, Online Solar Permitting

The National Renewable Energy Laboratory (NREL) led a collaborative effort to develop the Solar Automated Permit Processing Plus (SolarAPP+), a no-cost solar permitting software solution to address residential solar photovoltaic (PV) permitting resource constraints and streamline solar adoption processes among authorities having jurisdiction (AHJs). The SolarAPP+ is an online portal that automates permit plan review, enabling an instant permit approval process for code-compliant residential PV systems. Based on national model building, electrical, and fire codes, the SolarAPP+ automatically performs a compliance check of permit inputs against code requirements and produces an inspection checklist that can be used to verify installation practices, workmanship, and adherence to the approved design. NREL conducted a two-phase pilot with five participating AHJs and 16 solar contractors, spanning from November 2020 through December 2021, evaluating the ability of SolarAPP+ to deliver instant permits and its impact on four critical areas within each AHJ: permit review timelines; solar adoption timelines; AHJ time saved; and inspection results. The pilot confirmed that SolarAPP+ reduced permit review times to less than one day, reduced solar adoption timelines by an average of 12 days, saved an estimated 2,067 staff hours, and had comparable inspection results to those found in traditional permitting. The pilot further identified key lessons for improving SolarAPP+, including ways to streamline SolarAPP+ adoption, development of training resources, and expansion of supported products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer

Determining the Z-R relationship (where Z is the radar reflectivity factor and R is rainfall rate) from disdrometer data has been and is a common goal of cloud physicists and radar meteorology researchers. The usefulness of this quantity has traditionally been limited since radar represents a volume measurement, while a disdrometer corresponds to a point measurement. To solve that problem, a 3D-DSD (drop-size distribution) method of determining an equivalent 3D Z-R was developed at the University of Central Florida and tested at the Kennedy Space Center, FL. Unfortunately, that method required a minimum of three disdrometers clustered together within a microscale network (.1-km separation). Since most commercial disdrometers used by the radar meteorology/cloud physics community are high-cost instruments, three disdrometers located within a microscale area is generally not a practical strategy due to the limitations of these kinds of research budgets. A relatively simple modification to the 3D-DSD algorithm provides an estimate of the 3D-DSD and therefore, a 3D Z-R measurement using a single disdrometer. The basis of the horizontal extrapolation is mass conservation of a drop size increment, employing the mass conservation equation. For vertical extrapolation, convolution of a drop size increment using raindrop terminal velocity is used. Together, these two independent extrapolation techniques provide a complete 3DDSD estimate in a volume around and above a single disdrometer. The estimation error is lowest along a vertical plane intersecting the disdrometer position in the direction of wind advection. This work demonstrates that multiple sensors are not required for successful implementation of the 3D interpolation/extrapolation algorithm. This is a great benefit since it is seldom that multiple sensors in the required spatial arrangement are available for this type of analysis. The original software (developed at the University of Central Florida, 1998.- 2000) has also been modified to read standardized disdrometer data format (Joss-Waldvogel format). Other modifications to the software involve accounting for vertical ambient wind motion, as well as evaporation of the raindrop during its flight time.

Lane, John↗

Measured and estimated performance of a fleet of shaded photovoltaic systems with string and module-level inverters

Shade obstructions can significantly impact the performance of photovoltaic (PV) systems. Although there are many models for partially shaded PV arrays, there is a lack of information available regarding their accuracy and uncertainty when compared with actual field performance. This work assesses the recorded performance of 46 residential PV systems, equipped with either string-level or module-level inverters, under a variety of shading conditions. We compare their energy production data to annual PV performance predictions, with a focus on the practical models developed here for National Renewable Energy Laboratory's system advisor model software. This includes assessment of shade extent on each PV system by using traditional onsite surveys and newer 3D obstruction modelling. The electrical impact of shade is modelled by either a nonlinear performance model or assumption of linear impact with shade extent, depending on the inverter type. When applied to the fleet of residential PV systems, performance is predicted with median annual bias errors of 2.5% or less, for systems with up to 20% estimated shading loss. The partial shade models are not found to add appreciable uncertainty to annual predictions of energy production for this fleet of systems but do introduce a monthly root-mean-square error of approximately 4%-9% due to seasonal effects. Here the use of a detailed 3D model results in similar or improved accuracy over site survey methods, indicating that, with proper description of shade obstructions, modelling of partially shaded PV arrays can be done completely remotely, potentially saving time and cost.

14 SOLAR ENERGY↗

Development of a Low-Cost Sub-Scale Aircraft for Flight Research: The FASER Project

An inexpensive unmanned sub-scale aircraft was developed to conduct frequent flight test experiments for research and demonstration of advanced dynamic modeling and control design concepts. This paper describes the aircraft, flight systems, flight operations, and data compatibility including details of some practical problems encountered and the solutions found. The aircraft, named Free-flying Aircraft for Sub-scale Experimental Research, or FASER, was outfitted with high-quality instrumentation to measure aircraft inputs and states, as well as vehicle health parameters. Flight data are stored onboard, but can also be telemetered to a ground station in real time for analysis. Commercial-off-the-shelf hardware and software were used as often as possible. The flight computer is based on the PC104 platform, and runs xPC-Target software. Extensive wind tunnel testing was conducted with the same aircraft used for flight testing, and a six degree-of-freedom simulation with nonlinear aerodynamics was developed to support flight tests. Flight tests to date have been conducted to mature the flight operations, validate the instrumentation, and check the flight data for kinematic consistency. Data compatibility analysis showed that the flight data are accurate and consistent after corrections are made for estimated systematic instrumentation errors.

Owens, Donald B.↗

Empirical Validation of UBEM: An Assessment of Bias in Urban Building Energy Modeling for Chicago

Residential and commercial buildings currently account for 30% of total global final energy consumption. Urban-scale building energy modeling (UBEM) can enable scalable investments and unlock building improvements by quantifying energy, demand, emissions, and cost reductions of specific measures or packages for building-specific technologies in large geographic regions. While the sophistication of UBEM data sources and technologies have increased dramatically in the past decade, there remains a knowledge gap for empirical validation and sources of bias between building-specific energy models and measured data at varying geographic scales.As UBEM continues to develop, systemic analysis of accuracy, bias, and limitations of the resulting models is necessary to inform best practices and move toward standardization. These are characterized for the Automatic Building Energy Modeling (AutoBEM) software suite with an initial case study involving metered electricity consumption data from 247,188 buildings in Chicago, Illinois, USA - averaged across years 2019-2021 - compared to the following datasets: (1) the AutoBEM-generated nation-scale Model America version 2 (MAv2) data for 596,064 buildings, (2) tax assessor data for 579,829 buildings, (3) tax assessor data filled with MAv2, and (4) 102 representative dynamic archetypes. The accuracy is reported for every building type and vintage combination, along with multiple sources of bias for unique building descriptors. The AutoBEM simulation workflow produced energy consumption estimates that closely match aggregated metered electricity consumption data for different types of buildings constructed during various time periods at the city scale - with initial normalized mean bias error of 10.9%, and 1.1% after removing outliers. Contribution of statistically significant factors including building type, land use, age, and size to variance in UBEM bias is quantified.

Garg, Ankur↗

Multiversion software reliability through fault-avoidance and fault-tolerance

In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.

Vouk, Mladen A.↗

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗

Building commissioning costs and savings across three decades and 1500 North American buildings

B.V. Building commissioning (Cx) is a process for assuring efficient building operations that can be applied to new construction and existing buildings, resulting in energy and non-energy benefits. Quantifying the benefits of commissioning is challenging, but a 2009 study of 643 commercial buildings provided a solid initial data set to which we added 839 additional buildings for a significantly expanded and updated meta-analysis representing 34.7 million square meters (373 million square feet) of floor area. Since 2009 the commissioning industry has continued to grow, driven by building codes, utility programs, and rising awareness of commissioning benefits. In parallel, building controls have become more sophisticated, and analytics software has emerged to assist with commissioning. We find that delivery mechanism and market segment are key determinants of outcomes, although significant and cost-effective savings are found across the spectrum. Median primary energy savings for Cx projects in existing buildings ranged from 5 percent for those conducted under utility programs, 9 percent for monitoring-based commissioning utility programs (i.e., augmented with submetering and diagnostics), and 14 percent for Cx projects outside of utility programs. Across all project types, median savings ranged from 3 percent for the lodging market segment to 16 percent for public order and safety facilities. Outcomes did not vary significantly by building size or by market segment. Energy savings are rarely estimated for new construction commissioning. We found that the median costs of Cx were lower for the 2018 sample than for the 2009 sample—$\$$2.85 per square meter ($\$$0.26 per square foot) for existing buildings (a 33 percent reduction) and $\$$8.78 per square meter ($\$$0.82 per square foot) for new construction (a reduction of almost 50 percent). The median simple payback time for existing buildings was 1.7 years, with a 25th–75th percentile range of 0.8–3.5 years. Overall, this article summarizes these and other key findings, and discusses how the 2018 data reflects shifts in commissioning practice and outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗

Technical Maturity Assessment of Risk-Informed Safety Analysis Tools

Ensuring maximum safety while enhancing economic benefit is one of most important goal of In the of US Light Water Reactor Sustainability (LWRS) program. Optimization of the safety margins will provide best practice to achieve this goal which can also lead to cost reduction. Under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway has been focusing on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. One of the important activities of the pathway is to deploy risk-informed analysis tools to related nuclear industry to support precise representation of safety margins and factors that contribute to cost and safety. The tools therefore need highest technical maturity so that industry can use immediately with strong credibility. The tools should have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway, therefore, have been performing a comprehensive assessment of technical maturity and verification and validation (V&V) status of selected tools to improve adaptability to the industry. The technical maturity assessment includes three work scope: (a) define requirements based on risk-informed concept; (b) investigate and review development and V&V status for technical maturity assessment; and (c) identify technical gap and propose improvement to meet RISA toolkit requirements. The Requirement Traceability Matrix (RTM) concept was used to capture the requirements from user and developer of the project and/or software. The importance of each requirements was evaluated by Phenomena Identification and Ranking Technology (PIRT) which systematically gathers information and ranks the importance of the information. Finally, degree of the maturity was measured by Technology Readiness Level (TRL) for estimating the maturity of the technologies during the development and acquisition phase of certain technology. This paper summarizes development of assessment method and technical maturity evaluation of multi-purpose probabilistic risk analysis tool RAVEN.

, PIRT↗

Implementation of ANL’s Mechanics Based Evolutionary Fatigue Modeling Through ABAQUS-WARP3D Based High-Performance Computing Framework

This report presents an update on the environmental fatigue research that is being conducted at Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Argonne is developing a fully mechanistic fatigue evaluation approach without using empirical fatigue (S~N) curves. This approach is based on the fundamental concept of the time evolution of progressive fatigue damage rather than on the conventional S~N curve approaches using end-of-life data. In FY 2017, we performed extensive validation of this approach with respect to fatigue test data for 316 stainless steel [1]. This validation was performed for different loading cases, including constant, variable, and random amplitude. In the present FY 2018 semi-annual report, we present the further advances of Argonne’s environmental fatigue research work in the context for more practical applications. In this report, we discuss a methodology for fully mechanistic (i.e., not using S~N curves) fatigue life evaluation of reactor components subjected to realistic loading cycles, namely, design-basis loading cycles. The loading cycles include plant heat-up, full-power, and cool-down operations. As a test case, we considered a typical pressurized water reactor surge line, which is made of 316 SS. To perform the fatigue simulation for thousands of fatigue cycles in a computationally cost effective way, we modified our previous desktop-based finite element (FE) modeling approach to work in a high-performance computing (HPC) framework. For the HPC implementation, we developed a hybrid framework based on commercial FE software (ABAQUS), open-source FE software (WARP3D), and Argonne-developed evolutionary cyclic-plasticity modeling methods. We validated this HPC-based cycle-by-cycle damage model for the entire fatigue life of a Pressurized Water Reactor (PWR) surge line (SL) pipe with respect to assumed loading cycles. The simulated fatigue life was found to be 5855 cycles, which is 85% accurate as compared to the corresponding small-specimen-based experimental fatigue life (6914 cycles). Also, the simulated stress history captures the cyclic hardening and softening behavior of the material for entire fatigue cycles. The FE simulation of the PWR SL pipe was conducted in a reasonable time of 12.5 days. These results show the promise that a fully mechanistic (not using S~N curves) fatigue life evaluation of a safety-critical nuclear reactor component (or even other safety critical components like those in aircraft, aero-engines, etc.) is possible. We anticipate that this type of methodology will drastically reduce the uncertainly associated with conventional fatigue life estimates based on empirical S~N curves. We also proposed an FE model that is based on a hybrid full-component and single-element approach and that can readily be used by industry if HPC resources are not available. In this approach, a single-cycle FE simulation has to be performed first for the required loading cycle. Then, the resulting strain/stress profile at the hotspot (highest strain/stress location) is used as input strain/stress loading to the single-element FE model. The single-element FE model is run under multiple fatigue cycles as long as the failure criteria are achieved. The cycle number at failure gives the fatigue life of the component in question. This cost-effective framework does not require expensive HPC hardware and can be performed in a reasonable time by using a desktop computer. We demonstrated this approach with respect to PWR SL fatigue evaluation under two realistic design-basis loading cycles (simple and detailed). The associated results were validated with respect to test data obtained through fatigue testing of uniaxial specimens under the in-air condition at 300 °C. The approach is in the development stage and requires further improvement and validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Mars Sample Return Landed with Red Dragon

A Mars Sample Return (MSR) mission is the highest priority science mission for the next decade as recommended by the recent Decadal Survey of Planetary Science. However, an affordable program to carry this out has not been defined. This paper describes a study that examined use of emerging commercial capabilities to land the sample return elements, with the goal of reducing mission cost. A team at NASA Ames examined the feasibility of the following scenario for MSR: A Falcon Heavy launcher injects a SpaceX Dragon crew capsule and trunk onto a Trans Mars Injection trajectory. The capsule is modified to carry all the hardware needed to return samples collected on Mars including a Mars Ascent Vehicle (MAV), an Earth Return Vehicle (ERV) and Sample Collection and Storage hardware. The Dragon descends to land on the surface of Mars using SuperSonic Retro Propulsion (SSRP) as described by Braun and Manning [IEEEAC paper 0076, 2005]. Samples are acquired and deliverd to the MAV by a prelanded asset, possibly the proposed 2020 rover. After samples are obtained and stored in the ERV, the MAV launches the sample-containing ERV from the surface of Mars. We examined cases where the ERV is delivered to either low Mars orbit (LMO), C3 = 0 (Mars escape), or an intermediate energy state. The ERV then provides the rest of the energy (delta V) required to perform trans-Earth injection (TEI), cruise, and insertion into a Moon-trailing Earth Orbit (MTEO). A later mission, possibly a crewed Dragon launched by a Falcon Heavy (not part of the current study) retrieves the sample container, packages the sample, and performs a controlled Earth re-entry to prevent Mars materials from accidentally contaminating Earth. The key analysis methods used in the study employed a set of parametric mass estimating relationships (MERs) and standard aerospace analysis software codes modified for the MAV class of launch vehicle to determine the range of performance parameters that produced converged spacecraft designs capable of meeting mission requirements. Subsystems modeled in this study included structures, power system, propulsion system, nose fairing, thermal insulation, actuation devices, and GN&C. Best practice application of loads and design margins for all resources were used. Both storable and cryogenic propellant systems were examined. The landed mass and lander capsule size provide boundary conditions for the MAV design and packaging. We estimated the maximum mass the Dragon capsule is capable of landing. This and the volume capability to store the MAV was deduced from publically available data from SpaceX as well as our own engineering and aerodynamic estimates. Minimum gross-liftoff mass (GLOM) for the MAV were obtained for configurations that used pump-fed storable bi-propellant rocket engines for both the MAV and the ERV stage. The GLOM required fits within our internal estimate of the mass that Dragon can land at low elevation/optimal seasons on Mars. Based on the analysis, we show that a single Mars launch sample return mission is feasible using current commercial capabilities to deliver the return spacecraft assets.

Mars Ascent Vehicle (MAV)↗

FUSRAP Case Study - Benefits and Lessons Learned from Implementation of a Modern Data Solution at Maywood - 18399

This paper focuses on data production and management practices dating back to 1999 that continue to evolve to support the project today. In 2000, the FUSRAP Maywood Project began using a software environmental data management system and laboratory information management system, developed by a single database administrator (DA) and authored in Microsoft Access{sup TM} (MS Access). The original databases included basic functionality including sample number assignment and label generation, tracking of LIMS gamma spec QC and assignment of basic qualifiers and basic database queries. The DA continued over the next fifteen years to refine the EDMS/LIMS by integrating project-specific data evaluation guidance document processes and Quality Assurance/Quality Control (QA/QC) charting and excursion warning tools. With the retirement of the original DA, the U.S. Army Corps of Engineers (USACE)-Cabrera Team procured and implemented a commercial-leaning solution using modern database tools and an established EDMS vendor. For the database transition process, the project team established and configured the new EDMS/LIMS with basic architecture and accessibility; evaluated existing workflows; established/revised LIMS and EDMS-related documentation (manuals and procedures); and conducted dry runs and validation testing. The overall team coordinated closely to facilitate a seamless transition from initial assessment and authoring, to data migration, and finally to resumption of normal ongoing operations. Key features of the new EDMS Subcontractor's software included lookup tables, an import wizard, data checking options and unique indexes. Since the database systems became operational, the technical staff gathered useful feedback from end users (e.g., lab staff, field engineers, task managers, and the third-party data validator) to refine the EDMS/LIMS operation. This feedback triggered improvements in the performance of onsite laboratory qualification forms, promoted consistency in sample ID numbers between the database sample planning screens and field chain-of-custodies, corrected bugs in the LIMS Duplicate Evaluation Report, eliminated data import issues such as blank, inconsistent or missing data from key fields. One of the advantages of the commercial database solution was that it allowed the project to cut cost over time due to the lower cost of database maintenance provided by the commercial database vendor versus the cost of an on-staff DA. Cost savings are estimated at $40,000 per year. There were also indirect cost savings resulting from implementation of the new database since it allowed better integration of the LIMS and EDMS. While there will always be challenges associated with long term records/data management for any old remediation site, the Maywood Team's approach to an upgraded EDMS/LIMS implementation serves as one element of the overall effort to enhance the integrity and reproducibility of critical data that supports the remediation program while at the same time, more effectively using available resources. These lessons-learned will enhance implementation of cost-effective solutions for similar environmental remediation sites. (authors)

97 MATHEMATICS AND COMPUTING↗