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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The analysis used was based on instrumented system data monitored and collected for at least one full season of operation. The long-term field performance of the installed system is described. Technical contributions to the definition of techniques and requirements for solar energy system design are given.
With the proliferation of complex digital systems on aircraft, the need to accurately predict system performance early in the system design cycle becomes imperative. In the past, system designers have relied on ad hoc methods for evaluating performance issues. This has produced systems that have not always worked as originally intended. To alleviate these design deficiencies, formal methods, with supporting tools, must be adhered to during the system design process. The use of performance modeling tools is becoming widely accepted as a way to address timing considerations of system design. An additional incentive for the use of these tools is that they allow the system architect to analyze system component interactions (i.e., bus contention, contention of functions for a processing site, and system repair activity on application performance). This inherent flexibility can result in an explicit specification of the system architecture. This paper addresses a method that supports performance modeling of fault tolerant systems using a discrete event simulation tool. An additional focus is on lessons learned from analyzing these classes of problems. The methodology and supporting work provide system architects with the capability to specify candidate architectures and accurately predict their performance in the early stages of design, where changes to system design is most cost effective. The work has been supported under NASA contract NAS1-18099. Integrated Airframe Propulsion Control System Architecture (IAPSA II). This contract addresses methodology, analysis, and detailed design of integrated control system architectures suitable for high-performance aircraft of the 1990's.
Nuclear Electric Propulsion (NEP) mission performance is strongly affected by system performance. Power and propulsion system specific mass, specific impulse, and efficiency all combine to determine the performance limits for a given mission. Thruster technology determines the specific impulse and efficiency of the system. The effects of these parameters on the mission performance of NEP systems relative to other concepts was analyzed to give guidance to thruster development goals for a range of missions: Lunar Cargo, Mars Cargo, and Mars Piloted. Mission sensitivities to system parameters are discussed, and technology requirements are identified for each mission.
The Advanced Electric Propulsion System (AEPS) program will develop a flight 13kW Hall thruster propulsion system based on NASA's HERMeS thruster. The AEPS system includes the Hall Thruster, the Power Processing Unit (PPU) and the Xenon Flow Controller (XFC). These three primary components must operate together to ensure that the system generates the required combinations of thrust and specific impulse at the required system efficiencies for the desired system lifetime. At the highest level, the AEPS system will be integrated into the spacecraft and will receive power, propellant, and commands from the spacecraft. Power and propellant flow rates will be determined by the throttle set points commanded by the spacecraft. Within the system, the major control loop is between the mass flow rate and thruster current, with time-dependencies required to handle all expected transients, and additional, much slower interactions between the thruster and cathode temperatures, flow controller and PPU. The internal system interactions generally occur on shorter timescales than the spacecraft interactions, though certain failure modes may require rapid responses from the spacecraft. The AEPS system performance model is designed to account for all these interactions in a way that allows evaluation of the sensitivity of the system to expected changes over the planned mission as well as to assess the impacts of normal component and assembly variability during the production phase of the program. This effort describes the plan for the system performance model development, correlation to NASA test data, and how the model will be used to evaluate the critical internal and external interactions. The results will ensure the component requirements do not unnecessarily drive the system cost or overly constrain the development program. Finally, the model will be available to quickly troubleshoot any future unforeseen development challenges.
This report presents a performance analysis of 75 photovoltaic systems based on PV system production data collected as part of a FEMP Federal PV Performance Assessment project combined with co-incident insolation, and ambient temperature to analyze how actual performance compares with a performance model. FEMP collaborated with 17 Federal agencies and sub-agencies to collect the information required to analyze the performance of each system. The systems represent a total capacity of 30,714 kW and range in size from 1 kW to 4,043 kW, with an average size of 410 kW, and were installed between 2011 and 2020. The data is analyzed for Key Performance Indicators, Availability, Performance Ratio and Energy Ratio by comparing the measured production data to model production data. The System Advisor Model (SAM) combines a description of the system (such as inverter capacity, de-rating for temperature, balance-of-system efficiency) with environmental parameters (coincident solar and temperature data) to calculate predicted performance. The performance metrics are calculated by lining up the measured production data with the model estimate on an hour-by-hour, day-by-day, or month-by-month basis (depending on the interval resolution of the production data). A report with system description, photo of the system, special assumptions made for the site, graph of measured production and model production, table of key performance indicators, and links to O&M resources that might improve performance was produced and delivered to site and agency staff with a short on-line briefing.
As automated space systems become more complex, autonomous, and opaque to the flight crew, it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed that are related to total system validation. An evaluative throughput model is presented which can be used to generate a human operator-related benchmark or figure of merit for a given system which involves humans at the input and output ends as well as other automated intelligent agents. The concept of sustained and accurate command/control data information transfer is introduced. The first two input parameters of the model involve nominal and off-nominal predicted events. The first of these calls for a detailed task analysis while the second is for a contingency event assessment. The last two required input parameters involving actual (measured) events, namely human performance and continuous semi-automated system performance. An expression combining these four parameters was found using digital simulations and identical, representative, random data to yield the smallest variance.
The philocophy and the objectives of the telemetry system performance tests (SPTs) are discussed to demonstrate the benefits gained by performing these tests. The test procedure and test software are included. The results and the status of the Network Telemetry system are summarized.
The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center is planning a customized approach to quantify human spaceflight performance changes with respect to changes to the CHP system functions and capabilities. Using the Directed Acyclic Graphs (DAG) initiated by NASA’s Human Systems Risk Board (HSRB) [1], the team is surveying potential candidate models and novel strategies that generate metrics suitable for supporting decision making related to how the CHP system may influence human system performance risk. One such investigation includes classic Human Reliability Analysis (HRA) models. Traditionally, HRA methods estimate the occurrence of human errors and their impact on the success of an activity when designing and operating a system. While humans perceive, interpret, decide on, and carry out a course of action, the factors affecting performance and error likelihood are commonly referred to as performance shaping factors (PSFs). Originally developed to alleviate safety concerns related to nuclear power plant operations, HRA methods such as THERP [2] and CREAM [3] dismantle an activity into tasks, requiring elemental steps to be executed, and assess their failure due to predefined PSFs. In this study, we compare generic HRA methods and those that incorporate some human spaceflight aspects, such as sleep conditions (SCREAM [4]), with respect to how they may be adopted to capture performance with an intention to mitigate detrimental outcomes elucidated by the HSRB DAGs. We suggest strategies to quantify astronaut performance specific to spaceflight activities and illustrate how such concepts may help in optimizing the CHP system capabilities with respect to Artemis missions.
The Integrated Main Propulsion System (MPS) Performance Reconstruction process provides the MPS post-flight data files needed for postflight reporting to the project integration management and key customers to verify flight performance. This process/model was used as the baseline for the currently ongoing Space Launch System (SLS) work. The process utilizes several methodologies, including multiple software programs, to model integrated propulsion system performance through space shuttle ascent. It is used to evaluate integrated propulsion systems, including propellant tanks, feed systems, rocket engine, and pressurization systems performance throughout ascent based on flight pressure and temperature data. The latest revision incorporates new methods based on main engine power balance model updates to model higher mixture ratio operation at lower engine power levels.
The critical system elements of an optical imaging system are identified and a method for an initial assessment of system performance is presented. A generalized imaging system is defined. A system analysis is considered, followed by a component analysis. An example of the method is given using a film imaging system.
DSN telemetry system performance is analyzed based on convolutionally coded data for the short constraint length 7:1/2 codes at low bit rates, 8 to 2,048 bits per second, obtained from CTA 21 for the S-band configuration. The results indicate that a loss of one or more decibels in the system performance may be expected due to system degradation. Also, burst error lengths up to 100 bits may not be unusual in actual operational situations.
The radiometric and spectral system performance of space-borne infrared radiometers is generally specified and analyzed under strictly cloud-free, spatially uniform and warm conditions, with the assumption that the observed performance applies to the full dynamic range under clear and cloudy conditions and that random noise cancels for the evaluation of the radiometric accuracy. Such clear conditions are found in only one percent of the data. Ninety nine percent of the data include clouds, which produce spatially highly non-uniform scenes with 11 micrometers window brightness temperatures as low as 200K. We use AIRS and IASI radiance spectra to compare system performance under clear and a wide range of cloudy conditions. Although the two instruments are in polar orbits, with the ascending nodes separated by four hours, daily averages already reveal surprisingly similar measurements. The AIRS and IASI radiometric performance based on the mean of large numbers of observation is comparable and agrees within 200 mK over a wide range of temperatures. There are also some unexpected differences at the 200 -500 mK level, which are of significance for climate applications. The results were verified with data from July 2007 through January 2010, but many can already be gleaned from the analysis of a single day of data.
A hot solar heating and hot water system's operational performance from April 1979 through March 1980 is evaluated. The space heating and hot water loads were near expected values for the year. Solar energy provided 43 percent of the space heating and 53 percent of the hot water energy. The system did not meet the total system solar fraction design value of 69 percent because of a combination of higher estimated space heating load than was actually encountered and the apportioning of solar energy between the space heating and the domestic hot water loads. System losses and high building temperatures also contributed to this deviation. Total net savings were 23.072 million BTUs. Most of the energy savings came during the winter months, but hot water savings were sufficient to justify running the system during the summer months.
Results found by applying a predictive model to a particular system (University of Maryland Computer Center's Univak 1100/42) are presented. Given the correct model parameters, the system performance from the model closely matches the actual system observed performance. However, the major application of system modeling is the prediction of performance when the system configuration is altered. The prediction results presented are disappointing but useful with the major problem traced to parametric instabilities. The interactions between the user demands, overhead activities, and device characteristics must be considered in developing system models.
A three axis inertial system was packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization and iteration rate. The strapdown performance and tradeoff studies conducted include: (1) Compensation models and techniques for the inertial instrument first-order error terms were developed and compensation effectivity was demonstrated in four basic environments; single and multi-axis slew, and single and multi-axis oscillatory. (2) The theoretical coning bandwidth for the first-order quaternion algorithm expansion was verified. (3) Gyro loop quantization was identified to affect proportionally the system attitude uncertainty. (4) Land navigation evaluations identified the requirement for accurate initialization alignment in order to pursue fine grain navigation evaluations.
A three axis inertial system is packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization iteration rate. The strapdown performance and tradeoff studies conducted in this program are discussed.
Apollo propulsion performance, discussing system, flight and ground tests data
Structural flexibility of robotic manipulators becomes significant and limits the performance of a control system when manipulators are large structures, manipulating on large payloads, and/or operating at high speeds. The question of when a manipulator can be considered rigid or must be considered flexible is studied as a function of manipulator dynamics and task characteristics. Results are interpreted in simple quantitative forms which can be used as design and analysis tools to decide whether or not the manipulator flexibility will be a significant factor for a given task condition. The limitations imposed by the manipulator flexibility on the joint variable feedback control system performance is determined using linear and nonlinear methods. The closed loop eigenstructure behavior of finite dimensional models under joint variable feedback is studied and results are compared with the previously reported results.