Engineering topics

Rusick, Jeffrey J.

Publications and source records attributed to Rusick, Jeffrey J..

9 records

NASA NTRS2015

Radioisotope Power System Pool Concept

Advanced Radioisotope Power Systems (RPS) for NASA deep space science missions have historically used static thermoelectric-based designs because they are highly reliable, and their radioisotope heat sources can be passively cooled throughout the mission life cycle. Recently, a significant effort to develop a dynamic RPS, the Advanced Stirling Radioisotope Generator (ASRG), was conducted by NASA and the Department of Energy, because Stirling based designs offer energy conversion efficiencies four times higher than heritage thermoelectric designs; and the efficiency would proportionately reduce the amount of radioisotope fuel needed for the same power output. However, the long term reliability of a Stirling based design is a concern compared to thermoelectric designs, because for certain Stirling system architectures the radioisotope heat sources must be actively cooled via the dynamic operation of Stirling converters throughout the mission life cycle. To address this reliability concern, a new dynamic Stirling cycle RPS architecture is proposed called the RPS Pool Concept.

Power↗

NASA NTRS2013

Advanced Stirling Radioisotope Generator Life Certification Plan

An Advanced Stirling Radioisotope Generator (ASRG) power supply is being developed by the Department of Energy (DOE) in partnership with NASA for potential future deep space science missions. Unlike previous radioisotope power supplies for space exploration, such as the passive MMRTG used recently on the Mars Curiosity rover, the ASRG is an active dynamic power supply with moving Stirling engine mechanical components. Due to the long life requirement of 17 years and the dynamic nature of the Stirling engine, the ASRG project faced some unique challenges trying to establish full confidence that the power supply will function reliably over the mission life. These unique challenges resulted in the development of an overall life certification plan that emphasizes long-term Stirling engine test and inspection when analysis is not practical. The ASRG life certification plan developed is described.

Rusick, Jeffrey J.↗

NASA NTRS2013

Advanced Stirling Radioisotope Generator Life Certification Plan

Rusick, Jeffrey J.↗

NASA NTRS2005

Probabilistic Analysis Techniques Applied to Complex Spacecraft Power System Modeling

Electric power system performance predictions are critical to spacecraft, such as the International Space Station (ISS), to ensure that sufficient power is available to support all the spacecraft s power needs. In the case of the ISS power system, analyses to date have been deterministic, meaning that each analysis produces a single-valued result for power capability because of the complexity and large size of the model. As a result, the deterministic ISS analyses did not account for the sensitivity of the power capability to uncertainties in model input variables. Over the last 10 years, the NASA Glenn Research Center has developed advanced, computationally fast, probabilistic analysis techniques and successfully applied them to large (thousands of nodes) complex structural analysis models. These same techniques were recently applied to large, complex ISS power system models. This new application enables probabilistic power analyses that account for input uncertainties and produce results that include variations caused by these uncertainties. Specifically, N&R Engineering, under contract to NASA, integrated these advanced probabilistic techniques with Glenn s internationally recognized ISS power system model, System Power Analysis for Capability Evaluation (SPACE).

Hojnicki, Jeffrey S.↗

NASA NTRS2004

Probabilistic Physics-Based Risk Tools Used to Analyze the International Space Station Electrical Power System Output

This paper describes the methods employed to apply probabilistic modeling techniques to the International Space Station (ISS) power system. These techniques were used to quantify the probabilistic variation in the power output, also called the response variable, due to variations (uncertainties) associated with knowledge of the influencing factors called the random variables. These uncertainties can be due to unknown environmental conditions, variation in the performance of electrical power system components or sensor tolerances. Uncertainties in these variables, cause corresponding variations in the power output, but the magnitude of that effect varies with the ISS operating conditions, e.g. whether or not the solar panels are actively tracking the sun. Therefore, it is important to quantify the influence of these uncertainties on the power output for optimizing the power available for experiments.

Patel, Bhogila M.↗

NASA NTRS2003

Probabilistic Analysis of Solid Oxide Fuel Cell Based Hybrid Gas Turbine System

The emergence of fuel cell systems and hybrid fuel cell systems requires the evolution of analysis strategies for evaluating thermodynamic performance. A gas turbine thermodynamic cycle integrated with a fuel cell was computationally simulated and probabilistically evaluated in view of the several uncertainties in the thermodynamic performance parameters. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the uncertainties in the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of criteria for gas turbine performance.

Gorla, Rama S. R.↗

NASA NTRS2002

Probabilistic Analysis of Gas Turbine Field Performance

A gas turbine thermodynamic cycle was computationally simulated and probabilistically evaluated in view of the several uncertainties in the performance parameters, which are indices of gas turbine health. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design, enhance performance, increase system availability and make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in the gas turbine health determination and to the identification of both the most critical measurements and parameters. Probabilistic analysis aims at unifying and improving the control and health monitoring of gas turbine aero-engines by increasing the quality and quantity of information available about the engine's health and performance.

Gorla, Rama S. R.↗

NASA NTRS2002

NESTEM-QRAS: A Tool for Estimating Probability of Failure

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

Patel, Bhogilal M.↗

NASA NTRS2002

Probabilistic Study of Fluid Structure Interaction

A combustor liner was computationally simulated and probabilistically evaluated in view of the several uncertainties in the aerodynamic, structural, material and thermal variables that govern the combustor liner. The interconnection between the computational fluid dynamics code and the finite element structural analysis codes was necessary to couple the thermal profiles with structural design. The stresses and their variations were evaluated at critical points on the liner. Cumulative distribution functions and sensitivity factors were computed for stress responses due to the aerodynamic, mechanical and thermal random variables. It was observed that the inlet and exit temperatures have a lot of influence on the hoop stress. For prescribed values of inlet and exit temperatures, the Reynolds number of the flow, coefficient of thermal expansion, gas emissivity and absorptivity and thermal conductivity of the material have about the same impact on the hoop stress. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective.

Gorla, Rama S. R.↗