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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Removal Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide removal systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide removal systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗
NASA NTRS2019

Lynx x-ray microcalorimeter

Lynx is an x-ray telescope, one of four large satellite mission concepts currently being studied by NASA to be a flagship mission. One of Lynx’s three instruments is an imaging spectrometer called the Lynx x-ray microcalorimeter (LXM), an x-ray microcalorimeter behind an x-ray optic with an angular resolution of 0.5 arc sec and ∼2 sq. m of area at 1 keV. The LXM will provide unparalleled diagnostics of distant extended structures and, in particular, will allow the detailed study of the role of cosmic feedback in the evolution of the Universe. We discuss the baseline design of LXM and some parallel approaches for some of the key technologies. The baseline sensor technology uses transition-edge sensors, but we also consider an alternative approach using metallic magnetic calorimeters. We discuss the requirements for the instrument, the pixel layout, and the baseline readout design, which uses microwave superconducting quantum interference devices and high-electron mobility transistor amplifiers and the cryogenic cooling requirements and strategy for meeting these requirements. For each of these technologies, we discuss the current technology readiness level and our strategy for advancing them to be ready for flight. We also describe the current system design, including the block diagram, and our estimate for the mass, power, and data rate of the instrument.

Simon R. Bandler↗
NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Reduction Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide reduction systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide reduction systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRSDate not supplied

Design for Reliability (DfR) in Space Life Support

The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.

Reliability↗
NASA NTRS2022

X-57 Mod II Avionics Power Analysis

The X-57 Mod II Avionics Power Analysis was developed to provide the design requirements for the X-57 Avionics Power System. In the Mod II configuration, the two stock Tecnam P2006T Rotax engines are replaced with two electric motors. A high voltage traction battery (460 VDC nominal) supplies power for the motors. The Mod II avionics power design uses the stock Tecnam avionics power architecture as a baseline. The stock Tecnam power system utilizes three 12 VDC power sources, a battery and two alternators, to provided redundant avionics power. This redundancy was preserved in the X-57 avionics power architecture. A block diagram of the X-57 avionics system can be found in the “Mod II Architecture” worksheet of this documents. Since the X-57 electric motors do not have alternators or generators, two 13.8V DC Converters were added to replace the stock Tecnam alternators. Input power to these DC Converters is provide by the high voltage traction battery. The Tecnam stock lead acid battery was replaced with a Lithium Iron Phosphate (LiFePO4) battery. The Mod II Avionics Power Analysis provided the power requirements for the two 13.8V DC converters and the Lithium Iron Phosphate battery. Power requirement estimates for each subsystem used in this analysis were provided by manufacturer specifications, measured in the laboratory or provided by the subsystem design engineer. Typical power requirements and maximum power requirements were provided for each subsystem. The Mod II Avionics Power Systems consists of seven 13.8 VDC buses, two 28 VDC Buses and two 23 VDC buses. The avionics power requirements for Mod III configuration are the same as Mod II. The Mod III configuration replaces the stock Tecnam wing with a carbon fiber wing that is optimized for cruise conditions. The motors are located on the wingtips. The Mod IV Avionics Power Analysis is a separate analysis and is document number ANLYS-CEPT-032.

Keith Harris↗
NASA NTRSDate not supplied

System Modeling of a Lunar Molten Regolith Electrolysis Plant

Introduction: In-Situ Resource Utilization (ISRU) is the process of extracting local resources to produce commodities for propulsion, life support systems, and off-planet construction rather than transporting consumables from Earth. Molten Regolith Electrolysis (MRE) is a novel ISRU method of extracting oxygen gas and metal alloy from lunar regolith. The MRE process involves placing lunar regolith between two electrodes, through which current is passed, to melt the regolith and reduce the metal oxide constituents by direct electrolysis (e.g. FeO, SiO2, MgO, Al2O3) into oxygen gas and metal alloys. The oxygen is liquefied and used as propellant for landers, while the metals (e.g. Ferro-alloys) are further processed and used in structural building materials and parts manufacturing. A system model was developed that accounted for the major processes of an MRE plant (from excavation of raw materials to storage of products) to assess the feasibility of a lunar MRE plant. The System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team utilized its previously documented system sizing model, the Mission Analysis and Integration Tool (MAIT) [1] as framework of the system model. MAIT uses MATLAB/Simulink to integrate subsystem models into a complete system model of the MRE plant. Total mass, volume, and power requirements were computed for numerous iterations of a MRE plant. System Model: Figure 1: MRE Plant Block Diagram The regolith excavation model determines the mass and power needed to excavate sufficient regolith. The preheating auger initiates the regolith heating process before regolith enters the MRE re-actor to reduce the energy required to turn the solid into a molten liquid. The MRE reactor is modeled in COMSOL Multiphysics and based on the research by Dominguez, Sibille, and Schreiner [2, 3, 4]. This preliminary reactor model provides an accurate calculation of thermal equilibrium during electrochemical operation of the reactor system to assess the optimal mass and power required to process the inlet flow of regolith. The model also computes the outlet flowrates of oxygen and molten products. For this analysis, the primary components of the metal alloy considered were iron and silicon. The oxygen is then purified using an Yttrium Stabilized Zirconia (YSZ) electrode, followed by liquefaction using a 90K cryocooler to be stored as liquid oxygen in insulated cylindrical tanks. In future iterations of the system model, the molten metal tapped from the MRE reactor will undergo additional processing or refinement. However, downstream handling of metals is currently a technology gap that is missing a high TRL subsystem model. Therefore, for this analysis, the accumulated metal alloy stream terminates after leaving the MRE reactor. Study Goals: This analysis investigates multiple input variables to the system to determine the sensitivity of a (near) complete plant at full-scale. This preliminary investigation ran parametric sweeps on the MRE reactor geometry, electrical current supply, layers of multi-layer insulation (MLI) on the reactor, size of the electrodes in the oxygen purification model, and regolith composition (based on landing site location). Three production targets of oxygen (1,000, 10,000, and 50,000 kg/yr) were investigated for this analysis. The parametric sweeps conducted in this analysis provide valuable insight into the expected impact of the various model inputs on plant size. This information can be used to identify the most critical components of the plant and guide future decisions on allocating funding for research and development, providing subsystem developers with appropriate interfaces with downstream and upstream processes, and assessing the overall feasibility of MRE when compared to other ISRU plants. References: [1] Carlson, A. et al. (2024) ICES, ICES-2024-53. [2] Dominguez, D.A., and Sibille, L. (2011) AIAA, AIAA-2011-700. [3] Schreiner, S.S. (2015) MIT, Dissertation. [4] Schreiner, S.S. et al. (2016) ASR, 57(7), pp.1585-1603.

ISRU↗
DOE OSTI2020

Initial Assessment of Availability and Reliability for the PIP-II Superconducting Radio Frequency Linear Accelerator Facility

The Proton Improvement Plan -II (PIP-II) is a high intensity and high energy proton accelerator which will be used to support the neutrino program at Fermilab. The accelerator will deliver a 2 mA average beam current at a kinetic energy of 800 MeV. Due to the requirements from experiments, this accelerator is designed to be a highly reliable and available system. A target availability of the complete accelerator facility was prescribed to be 90%. An availability and reliability assessment of the accelerator was carried out to ascertain that the design can meet the target availability specification. The results were estimated for the nominal operational mode, when an 800 MeV beam is delivered on the target and for the critical operational mode, when a 600 MeV output beam was incident on the target. The design of a complete accel-erator system is a complex arrangement of a large number of components. To simplify the analysis, a few components were shortlisted and based on their functions, an accelerator model was created. The model is represented in the form of reliability block diagrams. Availability and reliability were estimated for each operational mode. To increase the availa-bility and reliability of the overall accelerator, redundancy of one cavity per section in the superconducting portion of the Linac was introduced.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Equivalent-Circuit Models of Grid-Forming IBRs for Electromagnetic-Transient Simulations: Preprint

We derive equivalent-circuit models of control- and physical-layer subsystems of grid-forming (GFM) inverter-based resources (IBRs) for electromagnetic-transient (EMT) simulations. Three different primary controllers are considered: droop, virtual synchronous machine (VSM), and dispatchable virtual oscillator control (dVOC). In addition, the models include cascaded voltage- and current-control loops, and LCL output filters. Simulations for a single-inverter setup and for a network of five inverters in a modified IEEE 14-bus topology are presented. The equivalent-circuit models simulated with analog electronic circuit-simulator software (in our case, LTspice) offer the same accuracy with up to 150x lower computational burden compared to block-diagram-based implementations in commercial off-the-shelf EMT software (in our case, MATLAB-Simulink).

circuit-equivalent model↗
DOE OSTI2024

Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context

Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase I Conceptual Study)

The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and the proposed system is an improvement over alternate low carbon dispatchable power options. Our demonstration will include 54 MWh of hydrogen storage. CO 2 capture inherent to the CHG process can capture 90% of the CO 2 (with upgrades to >98%) in a commercial system (~300 MWth) for sequestration or other uses. The hydrogen will be utilized in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with the existing Southern Company fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load. However, H 2 production is relatively constant by storing H 2 , and revenues are improved by arbitrage between use of low-cost off-peak variable electricity generation or use of stored H 2 under peak demand. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via system requirements review with the whole team. These requirements were then incorporated into/iterated with our Heat & Mass Balance models and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Our system generates power at 17.4% lower cost than other low carbon approaches for the H 2 generation, H 2 compression and storage, carbon sequestration, and HRSG added electricity production for a large-scale duct-fired system. Our team recommends completing the Phase II Pre-FEED study for the proposed system as the next step for the project and its tasks will achieve the overall objective and be ready to launch the FEED. The Pre-FEED tasks include updating the requirements, Concept of Operations, plant scope/process description, component modeling, system modeling, performance estimates, emission estimates, block flow diagrams, fluid/process conditions (PFD), utility usage, and facility sizing/definition. The approach will be to complete these updates in a greater level of detail for the selected site. The approach for developing the EIV is to use the updated results, including model outputs, for carbon dioxide and waste streams.

03 NATURAL GAS↗
DOE OSTI2025

Techno-Economic Analysis of Compressed Air Energy Storage and Hydrogen Production from Variable Renewable Energy

This study presents the techno-economic analysis (TEA) results of integrating electrolysis hydrogen (H 2 ) production, compressed air energy storage (CAES), and H 2 -fired combustion turbines in a high variable renewable energy (VRE) market environment. The inconsistent nature of VRE creates challenges for power producers in maintaining a stable electrical grid as it is increasingly utilized. The mission of the National Energy Technology Laboratory (NETL) is driving innovation and delivering energy solutions, and a multiangle approach involving H 2 production, energy storage, and next-level H 2 -fired combustion turbine generator (CTG) technologies could provide one solution for the nation’s growing electrical grid issues with increasing VRE sources. The H 2 production and CAES concept were investigated due to its ability to provide utility-scale H 2 -fueled power generation with large-scale energy storage capabilities. Two facilities with CAES and natural gas-fired CTGs (in McIntosh, Alabama, and Huntorf, Germany) have been operating for decades. In contrast, this study investigates the potential to replace the natural gas fuel with H 2 fuel. This concept has been publicly presented by both Siemens Energy and Bechtel Global Engineering, Construction & Project Management (Bechtel) at two different power generating levels. The CAES and air expansion/combustion turbine power generation in this study are primarily based on the Siemens Energy system (Bailie, Aug. 10-11, 2021) (Scheller, Feb. 21, 2023). The inclusion of a H 2 turboexpander generator is from Bechtel (Gülen, Sep. 6, 2022). A block flow diagram of the proposed process is illustrated in Exhibit ES-1.

08 HYDROGEN↗
NASA NTRS1989

Automated rejection of parasitic frequency sidebands in heterodyne-detection LIDAR applications

A technique is described for the detection of the sporadic onset of multiaxial mode behavior of a normally single-mode TEA CO2 laser. The technique is implemented using primarily commercial circuit modules; it incorporates a peak detector that displays the RF detector output on a digital voltmeter, and a LED bar graph. The technique was successfully demonstrated with an existing coherent atmospheric LIDAR facility utilizing an injection-seeded single-mode TEA CO2 laser. The block schematic diagram is included.

Esproles, Carlos↗
NASA NTRS1991

An SEU immune logic family

A new logic family, which is immune to single event upsets, is described. Members of the logic family are capable of recovery, regardless of the shape of the upsetting event. Glitch propagation from an upset node is also blocked. Logic diagrams for an Inverter, Nor, Nand, and Complex Gates are provided. The logic family can be implemented in a standard, commercial CMOS process with no additional masks. DC, transient, static power, upset recovery and layout characteristics of the new family, based on a commercial 1 micron CMOS N-Well process, are described.

Canaris, J.↗
NASA NTRS2011

LADEE Satellite Modeling and Simulation Development

As human activity on and around the Moon increases, so does the likelihood that our actions will have an impact on its atmosphere. The Lunar Atmosphere and Dust Environment Explorer (LADEE), a NASA satellite scheduled to launch in 2013, will orbit the Moon collecting composition, density, and time variability data to characterize the current state of the lunar atmosphere. LADEE will also test the concept of the "Modular Common Bus" spacecraft architecture, an effort to reduce both development time and cost by designing reusable, modular components for use in multiple missions with similar requirements. An important aspect of this design strategy is to both simulate the spacecraft and develop the flight code in Simulink, a block diagram-style programming language that allows easy algorithm visualization and performance testing. Before flight code can be tested, however, a realistic simulation of the satellite and its dynamics must be generated and validated. This includes all of the satellite control system components such as actuators used for force and torque generation and sensors used for inertial orientation reference. My primary responsibilities have included designing, integrating, and testing models for the LADEE thrusters, reaction wheels, star trackers, and rate gyroscopes.

Adams, Michael↗
NASA NTRS2020

Reliability Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering, with Model- Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. The recognized benefits to systems development include moving from document-centric information systems and document-centric project communication to a model-centric environment in which control of design changes in the life cycles is facilitated. In addition, a “single source of truth” about the system, that is up-to-date in all respects of the design, becomes the authoritative source of data and information about the system. This promotes consistency and efficiency in regard to integration of the system elements as the design emerges and thereby may further optimize the design. Therefore Reliability Engineers (REs) supporting NASA missions must be integrated into model-based engineering to ensure the outputs of their analyses are relevant and value-needed to the design, development, and operational processes for failure risks assessment and communication.

FMEA/FMECA↗