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At least 1,747 records · Page 97

Development of Models to Simulate Tracer Tests for Characterization of Enhanced Geothermal Systems

A recent report found that power and heat produced from enhanced (or engineered) geothermal systems (EGSs) could have a major impact on the U.S energy production capability while having a minimal impact on the environment. EGS resources differ from high-grade hydrothermal resources in that they lack sufficient temperature distribution, permeability/porosity, fluid saturation, or recharge of reservoir fluids. Therefore, quantitative characterization of temperature distributions and the surface area available for heat transfer in EGS is necessary for the design and commercial development of the geothermal energy of a potential EGS site. The goal of this project is to provide integrated tracer and tracer interpretation tools to facilitate this characterization. This project was initially focused on tracer development with the application of perfluorinated tracer (PFT) compounds, non-reactive tracers used in numerous applications from atmospheric transport to underground leak detection, to geothermal systems, and evaluation of encapsulated PFTs that would release tracers at targeted reservoir temperatures. After the 2011 midyear review and subsequent discussions with the U.S. Department of Energy Geothermal Technology Program (GTP), emphasis was shifted to interpretive tool development, testing, and validation. Subsurface modeling capabilities are an important component of this project for both the design of suitable tracers and the interpretation of data from in situ tracer tests, be they single- or multi-well tests. The purpose of this report is to describe the results of the tracer and model development for simulating and conducting tracer tests for characterizing EGS parameters.

EGS↗

Using computer graphics to design Space Station Freedom viewing

Viewing requirements were identified early in the Space Station Freedom program for both direct viewing via windows and indirect viewing via cameras and closed-circuit television (CCTV). These requirements reside in NASA Program Definition and Requirements Document (PDRD), Section 3: Space Station Systems Requirements. Currently, analyses are addressing the feasibility of direct and indirect viewing. The goal of these analyses is to determine the optimum locations for the windows, cameras, and CCTV's in order to meet established requirements, to adequately support space station assembly, and to operate on-board equipment. PLAID, a three-dimensional computer graphics program developed at NASA JSC, was selected for use as the major tool in these analyses. PLAID provides the capability to simulate the assembly of the station as well as to examine operations as the station evolves. This program has been used successfully as a tool to analyze general viewing conditions for many Space Shuttle elements and can be used for virtually all Space Station components. Additionally, PLAID provides the ability to integrate an anthropometric scale-modeled human (representing a crew member) with interior and exterior architecture.

Goldsberry, Betty S.↗

Simulation Modeling of an Earth Entry System and Solar Radiation Pressure Module Development

Several trajectory simulation tools are used to model different phases of the Approach, Entry, Descent and Landing (AEDL) phase of NASA’s Mars Sample Return Campaign. Working towards a single simulation tool that models all AEDL phases, this project utilizes Program to Optimize Simulated Trajectories II to simulate the 72-hour exoatmospheric phase of AEDL up till the point of Earth atmospheric entry. This involves developing a new feature forPOST2 that captures the forces and moments caused by solar radiation pressure(SRP). Generalizing the vehicle geometry as a combination of primitive shapes, a generalized SRP module was created and implemented into POST2. Trajectory solutions produced by POST2 were then successfully compared against independent solutions produced by the trajectory tool 42.

Program to Optimize Simulated Trajectories II↗

Core Noise: Implications of Emerging N+3 Designs and Acoustic Technology Needs

This presentation is a summary of the core-noise implications of NASA's primary N+3 aircraft concepts. These concepts are the MIT/P&W D8.5 Double Bubble design, the Boeing/GE SUGAR Volt hybrid gas-turbine/electric engine concept, the NASA N3-X Turboelectric Distributed Propulsion aircraft, and the NASA TBW-XN Truss-Braced Wing concept. The first two are future concepts for the Boeing 737/Airbus A320 US transcontinental mission of 180 passengers and a maximum range of 3000 nm. The last two are future concepts for the Boeing 777 transpacific mission of 350 passengers and a 7500 nm range. Sections of the presentation cover: turbofan design trends on the N+1.5 time frame and the already emerging importance of core noise; the NASA N+3 concepts and associated core-noise challenges; the historical trends for the engine bypass ratio (BPR), overall pressure ratio (OPR), and combustor exit temperature; and brief discussion of a noise research roadmap being developed to address the core-noise challenges identified for the N+3 concepts. The N+3 conceptual aircraft have (i) ultra-high bypass ratios, in the rage of 18 - 30, accomplished by either having a small-size, high-power-density core, an hybrid design which allows for an increased fan size, or by utilizing a turboelectric distributed propulsion design; and (ii) very high OPR in the 50 - 70 range. These trends will elevate the overall importance of turbomachinery core noise. The N+3 conceptual designs specify the need for the development and application of advanced liners and passive and active control strategies to reduce the core noise. Current engineering prediction of core noise uses semi-empirical methods based on older turbofan engines, with (at best) updates for more recent designs. The models have not seen the same level of development and maturity as those for fan and jet noise and are grossly inadequate for the designs considered for the N+3 time frame. An aggressive program for the development of updated noise prediction tools for integrated core assemblies as well as and strategies for noise reduction and control is needed in order to meet the NASA N+3 noise goals. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The SFW Reduced-Perceived-Noise Technical Challenge aims to develop concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. This reduction of aircraft noise is critical to enabling the anticipated large increase in future air traffic.

Hultgren, Lennart S.↗

From IMM to IMPACT: Enhanced Functionality for Exploration Missions

The Integrated Medical Model (IMM) is an evidence-based decision support tool used to assess medical risk and optimize medical systems for manned spaceflight missions. The IMM is baselined to the International Space Station (ISS) in terms of the spaceflight environment of low earth orbit and the ISS medical resource capability. IMPACT is the next generation evidence-based decision support tool currently under development by the Human Research Program to assess medical risk and optimize medical systems for future exploration missions to the moon and Mars. IMPACT is being designed to provide a comprehensive integrated suite of decision support tools for mission planners. This presentation will focus on the lessons learned from IMM and the enhanced functionalities of IMPACT.

E L Kerstman↗

NECAP 4.1: NASA's Energy-Cost Analysis Program input manual

The computer program NECAP (NASA's Energy Cost Analysis Program) is described. The program is a versatile building design and energy analysis tool which has embodied within it state of the art techniques for performing thermal load calculations and energy use predictions. With the program, comparisons of building designs and operational alternatives for new or existing buildings can be made. The major feature of the program is the response factor technique for calculating the heat transfer through the building surfaces which accounts for the building's mass. The program expands the response factor technique into a space response factor to account for internal building temperature swings; this is extremely important in determining true building loads and energy consumption when internal temperatures are allowed to swing.

Jensen, R. N.↗

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

High-Power Microwave Transmission and Mode Conversion Program

This is a final technical report for a long term project to develop improved designs and design tools for the microwave hardware and components associated with the DOE Plasma Fusion Program. We have developed basic theory, software, fabrication techniques, and low-power measurement techniques for the design of microwave hardware associated gyrotrons, microwave mode converters and high-power microwave transmission lines. Specifically, in this report we discuss our work on designing quasi-optical mode converters for single and multiple frequencies, a new method for the analysis of perturbed-wall waveguide mode converters, perturbed-wall launcher design for TE0n mode gyrotrons, quasi-optical traveling-wave resonator design for high-power testing of microwave components, and possible improvements to the HSX microwave transmission line.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Developing the Proof of Concept for the SERI QC Flag Translation

SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the second of six in the Data Quality and Uncertainty Integration project, develops the proof of concept, including programming in C and a collection of spreadsheet tools, for estimating the operational uncertainty from three-component solar irradiance measurements using information available from SERI QC. The report establishes a field reference for determining the operational uncertainty for each irradiance component based on the SERI QC coupling. Results demonstrate that the operational uncertainty estimates based on global irradiance best represent the collective results for all sky conditions.

14 SOLAR ENERGY↗

Space station common module power system network topology and hardware development

Candidate power system newtork topologies for the space station common module are defined and developed and the necessary hardware for test and evaluation is provided. Martin Marietta's approach to performing the proposed program is presented. Performance of the tasks described will assure systematic development and evaluation of program results, and will provide the necessary management tools, visibility, and control techniques for performance assessment. The plan is submitted in accordance with the data requirements given and includes a comprehensive task logic flow diagram, time phased manpower requirements, a program milestone schedule, and detailed descriptions of each program task.

Landis, D. M.↗

Experiences with Testing the Largest Ground System NASA Has Ever Built

In the 1980s, the National Aeronautics and Space Administration (NASA) embarked upon a major Earth-focused program called Mission to Planet Earth. The Goddard Space Flight Center (GSFC) was selected to manage and develop a key component - the Earth Observing System (EOS). The EOS consisted of four major missions designed to monitor the Earth. The missions included 4 spacecraft. Terra (launched December 1999), Aqua (launched May 2002), ICESat (Ice, Cloud, and Land Elevation Satellite, launched January 2003), and Aura (scheduled for launch January 2004). The purpose of these missions was to provide support for NASA s long-term research effort for determining how human-induced and natural changes affect our global environment. The EOS Data and Information System (EOSDIS), a globally distributed, large-scale scientific system, was built to support EOS. Its primary function is to capture, collect, process, and distribute the most voluminous set of remotely sensed scientific data to date estimated to be 350 Gbytes per day. The EOSDIS is composed of a diverse set of elements with functional capabilities that require the implementation of a complex set of computers, high-speed networks, mission-unique equipment, and associated Information Technology (IT) software along with mission-specific software. All missions are constrained by schedule, budget, and staffing resources, and rigorous testing has been shown to be critical to the success of each mission. This paper addresses the challenges associated with the planning, test definition. resource scheduling, execution, and discrepancy reporting involved in the mission readiness testing of a ground system on the scale of EOSDIS. The size and complexity of the mission systems supporting the Aqua flight operations, for example, combined with the limited resources available, prompted the project to challenge the prevailing testing culture. The resulting success of the Aqua Mission Readiness Testing (MRT) program was due in no small measure to re-structuring the traditional programmatic and technical approach to a more efficient and robust program. Programmatically, it meant gaining the endorsement, commitment, and cooperation of the numerous subsystem element managers and other stakeholder organizations. Technically, it required an MRT program that was agile, could rapidly adapt to requirements changes, and was flexible in its overall approach. Furthermore, this paper addresses the following questions: 1. What are the key ingredients (e.g., test tools, organization) needed to conduct a successful MRT program? 2. What distinguishes EOS MRT from the traditional system testing approach? 3. Where should the focus of testing be since it is infeasible to test every element or subsystem? 4. How can MRT be applied effectively to other systems or missions? To provide answers to these questions, this paper relies heavily on real-life, hands-on experiences ("lessons learned") gained during mission readiness testing of the Terra ground system and, most recently, the Aqua and ICESat missions. Moreover, this paper explores how lessons learned were turned into lessons applied for the upcoming Aura mission. Although derived from the EOS missions, MRT techniques and strategies can be applied to enhance the testing of other missions.

Lehtonen, Ken↗

Compressed Air Scoping Tool Teaches Energy Efficiency Best Practices

Standards and practices around compressed air systems are evolving as previous golden rules become outdated and unhelpful. One of the most referenced guidelines gives us the perfect example: The previous rule of thumb for compressed air storage – 1-3 gal/cfm1,2 – is now accepted to be 3-5 gal/cfm. This change in recommended storage is only one of many in the industry, resulting in industrial users lost in a sea of contradictory best practices. To help combat confusion and poor information sharing, a collaborative effort between Oak Ridge National Laboratory (ORNL) and the Department of Energy’s (DOE’s) Better Plants program created the Compressed Air (CA) Scoping Tool with the most up-to-date best practices in the industry (as of 2023). It can be used as a nonbiased, one-stop shop for best practice recommendations. The Excelbased tool is designed to be an initial step in understanding the operation of a compressed air system, a baselining tool enabling users to comprehend various aspects of a facility’s system from the production of compressed air to its application by end users.

42 ENGINEERING↗

Application of automated measurement and verification to utility energy efficiency program data

Trustworthy savings calculations are critical to convincing regulators of both the cost-effectiveness of energy efficiency program investments and their ability to defer supply-side capital investments. Today’s methods for measurement and verification (M&V) of energy savings constitute a significant portion of the total costs of energy efficiency programs. They also require time-consuming data acquisition. A spectrum of savings calculation approaches is used, with some relying more heavily on measured data and others relying more heavily on estimated, modeled, or stipulated data. The increasing availability of “smart” meters and devices that report near-real time data, combined with new analytical approaches to quantify savings, offers the potential to conduct M&V more quickly and at lower cost, with comparable or improved accuracy. Commercial energy management and information systems (EMIS) technologies are beginning to offer these ‘M&V 2.0’ capabilities, and program administrators want to understand how they might assist programs in quickly and accurately measuring energy savings. This paper presents the results of recent testing of the ability to use automation to streamline the M&V process. In this paper, we apply an automated whole-building M&V tool to historic data sets from energy efficiency programs to begin to explore the accuracy, cost, and time trade-offs between more traditional M&V, and these emerging streamlined methods that use high-resolution energy data and automated computational intelligence. For the data sets studied we evaluate the fraction of buildings that are well suited to automated baseline characterization, the uncertainty in gross savings that is due to M&V 2.0 tools’ model error, and indications of labor time savings, and how the automated savings results compare to prior, traditionally determined savings results. The results show that 70% of the buildings were well suited to the automated approach. In a majority of the cases (80%) savings and uncertainties for each individual building were quantified to levels above the criteria in ASHRAE Guideline 14. In addition the findings suggest that M&V 2.0 methods may also offer time-savings relative to traditional approaches. Lastly, we discuss the implications of these findings relative to the potential evolution of M&V, and pilots currently being launched to test how M&V automation can be integrated into ratepayer-funded programs and professional implementation and evaluation practice.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The ADAQ framework: An integrated toolkit for data acquisition and analysis with real and simulated radiation detectors

Here, the ADAQ framework is a collection of software tools that is designed to streamline the acquisition and analysis of radiation detector data produced in modern digital data acquisition (DAQ) systems and in Monte Carlo detector simulations. The purpose of the framework is to maximize user scientific pro-ductivity by minimizing the effort and expertise required to fully utilize radiation detectors in a variety of scientific and engineering disciplines. By using a single set of tools to span the real and simulation domains, the framework eliminates redundancy and provides an integrated workflow for high-fidelity comparison between experimental and simulated detector performance. Built on the ROOT data analysis framework, the core of the ADAQ framework is a set of Cþþ and Python libraries that enable high-level control of digital DAQ systems and detector simulations with data stored into standardized binary ROOT files for further analysis. Two graphical user interface programs utilize the libraries to create powerful tools: ADAQAcquisition handles control and readout of real-world DAQ systems and ADAQAnalysis provides data analysis and visualization methods for experimental and simulated data. At present, the ADAQ framework supports digital DAQ hardware from CAEN S.p.A. and detector simulations performed in Geant4; however, the modular design will facilitate future extension to other manufacturers and simulation platforms.

detector simulation↗

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

59 BASIC BIOLOGICAL SCIENCES↗

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

Requirements for a tool to aid in the development of expert systems for space station applications

The Space Station Program is currently in the early stages of design. The extended life of the program and the wide range of planned capabilities present NASA with a major challenge to make effective use of all available resources. Expert systems may represent one of the most important techniques NASA can use to improve performance and functionality of the Space Station. The recent growth in expert system applications has been spurred by the availability of commercial expert system development tools. These state-of-the-art tools provide multiple representation techniques, sophisticated user interfaces, and powerful development tools; allowing programmers to develop expert systems without requiring years of training in knowledge engineering. The requirements are described for a software tool to aid in the development and delivery of expert systems intended for use in the Space Station Program. The intent is to define a tool that would be useful for a very broad range of expert system applications.

Culbert, Chris↗