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At least 37 records · Page 2

Process-Based Cost Estimation for Ramjet/Scramjet Engines

Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

Singh, Brijendra↗

Multivariable Parametric Cost Model for Ground Optical Telescope Assembly

A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.

Stahl, H. Philip↗

Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.

Stahl, H. Philip↗

Engine System Loads Analysis Compared to Hot-Fire Data

Early implementation of structural dynamics finite element analyses for calculation of design loads is considered common design practice for high volume manufacturing industries such as automotive and aeronautical industries. However with the rarity of rocket engine development programs starts, these tools are relatively new to the design of rocket engines. In the NASA MC-1 engine program, the focus was to reduce the cost-to-weight ratio. The techniques for structural dynamics analysis practices, were tailored in this program to meet both production and structural design goals. Perturbation of rocket engine design parameters resulted in a number of MC-1 load cycles necessary to characterize the impact due to mass and stiffness changes. Evolution of loads and load extraction methodologies, parametric considerations and a discussion of load path sensitivities are important during the design and integration of a new engine system. During the final stages of development, it is important to verify the results of an engine system model to determine the validity of the results. During the final stages of the MC-1 program, hot-fire test results were obtained and compared to the structural design loads calculated by the engine system model. These comparisons are presented in this paper.

Frady, Gregory P.↗

Control structural interaction testbed: A model for multiple flexible body verification

Conventional end-to-end ground tests for verification of control system performance become increasingly complicated with the development of large, multiple flexible body spacecraft structures. The expense of accurately reproducing the on-orbit dynamic environment and the attendant difficulties in reducing and accounting for ground test effects limits the value of these tests. TRW has developed a building block approach whereby a combination of analysis, simulation, and test has replaced end-to-end performance verification by ground test. Tests are performed at the component, subsystem, and system level on engineering testbeds. These tests are aimed at authenticating models to be used in end-to-end performance verification simulations: component and subassembly engineering tests and analyses establish models and critical parameters, unit level engineering and acceptance tests refine models, and subsystem level tests confirm the models' overall behavior. The Precision Control of Agile Spacecraft (PCAS) project has developed a control structural interaction testbed with a multibody flexible structure to investigate new methods of precision control. This testbed is a model for TRW's approach to verifying control system performance. This approach has several advantages: (1) no allocation for test measurement errors is required, increasing flight hardware design allocations; (2) the approach permits greater latitude in investigating off-nominal conditions and parametric sensitivities; and (3) the simulation approach is cost effective, because the investment is in understanding the root behavior of the flight hardware and not in the ground test equipment and environment.

Chory, M. A.↗

Overview of NASA's Integrated Design and Engineering Analysis (IDEA)Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures) each of which performs their design and analysis in relative isolation from others. This is possible in most cases either because the amount of interdisciplinary coupling is minimal or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA s X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design & Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary launch vehicle configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, configuration, propulsion, aerodynamics, aerothermodynamics, trajectory, closure and structural analysis into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine based combined cycle (TBCC) first stage and reusable rocket second stage. This paper provides an overview of the development of the IDEA environment, a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗

Power Conditioning System Modelling for Nuclear Electric Propulsion

NASA LeRC is currently developing a Fortran based model of a complete nuclear electric propulsion (NEP) vehicle that would be used for piloted and cargo missions to the Moon or Mars. The proposed vehicle design will use either a Brayton or K-Rankine power conversion cycle to drive a turbine coupled with a rotary alternator. Two thruster types are also being studied, ion and magnetoplasmadynamic (MPD). In support of this NEP model, Rocketdyne developed a power management and distribution (PMAD) subroutine that provides parametric outputs for selected alternator operating voltages and frequencies, thruster types, system power levels, and electronics coldplate temperatures. The end-to-end PMAD model described is based on the direct use of the alternator voltage and frequency for transmitting power to either ion or MPD thrusters. This low frequency transmission approach was compared with dc and high frequency ac designs, and determined to have the lowest mass, highest efficiency, highest reliability and lowest development costs. While its power quality is not as good as that provided by a high frequency system, it was considered adequate for both ion and MPD engine applications. The low frequency architecture will be used as the reference in future NEP PMAD studies.

Metcalf, Kenneth J.↗

An Overview of NASA's Integrated Design and Engineering Analysis (IDEA) Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures), each of which performs design and analysis in relative isolation from others. This is possible, in most cases, either because the amount of interdisciplinary coupling is minimal, or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA's X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable, as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective, can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design and Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary designs for launch vehicle and high speed atmospheric flight configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, packaging, propulsion, trajectory, aerodynamics, aerothermodynamics, engine and airframe subsystem design, thermal and structural analysis, and vehicle closure into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA?s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine-based combined cycle (TBCC) first stage and a reusable rocket second stage. IDEA will be rolled out in generations, with each successive generation providing a significant increase in capability, either through increased analytic fidelity, expansion of vehicle classes considered, or by the inclusion of advanced modeling techniques. This paper provides the motivation behind the current effort, an overview of the development of the IDEA environment (including the contents and capabilities to be included in Generation 1 and Generation 2), and a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗

Estimating the Life Cycle Cost of Space Systems

A space system's Life Cycle Cost (LCC) includes design and development, launch and emplacement, and operations and maintenance. Each of these cost factors is usually estimated separately. NASA uses three different parametric models for the design and development cost of crewed space systems; the commercial PRICE-H space hardware cost model, the NASA-Air Force Cost Model (NAFCOM), and the Advanced Missions Cost Model (AMCM). System mass is an important parameter in all three models. System mass also determines the launch and emplacement cost, which directly depends on the cost per kilogram to launch mass to Low Earth Orbit (LEO). The launch and emplacement cost is the cost to launch to LEO the system itself and also the rockets, propellant, and lander needed to emplace it. The ratio of the total launch mass to payload mass depends on the mission scenario and destination. The operations and maintenance costs include any material and spares provided, the ground control crew, and sustaining engineering. The Mission Operations Cost Model (MOCM) estimates these costs as a percentage of the system development cost per year.

Life cycle cost↗

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and cost.

Kim, K. Han↗

Parametric Cost Modeling of a Mid-Lift-to-Drag Ratio Vehicle for Human Mars Entry, Descent, and Landing

Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically estimated after the preliminary vehicle and mission concepts have been designed. By automating the cost estimation process, the effect of any change in vehicle or mission design on the mission cost can be determined more rapidly. This paper uses the tool SAPE-C (Systems Analysis for Planetary Entry, Descent, and Landing-Cost). SAPE-C integrates the cost modeling software SEER-H (System Estimation and Evaluation of Resources-Hardware) with a number of systems analysis tools and enables large design tradespace exploration early in the design process. SAPE-C is used to analyze several tradespaces of the Mid-Lift-to-Drag ratio rigid entry vehicle for human Mars missions. Key findings include quantifying the impacts of payload, vehicle length, and main engine specific impulse on the overall cost of the vehicle, and how the payload per lander and number of landers affects the cost of a campaign to Mars.

Paul D Friz↗

Parametric Cost Modeling of a Mid-Lift-to-Drag Ratio Vehicle for Human Mars Entry, Descent, and Landing

Cost is one of the biggest obstacles to sending humans to Mars. However, spacecraft costs are typically estimated after the preliminary vehicle and mission concepts have been designed. By automating the cost estimation process, the effect of any change in vehicle or mission design on the mission cost can be determined more rapidly. This paper uses the tool SAPE-C (Systems Analysis for Planetary Entry, Descent, and Landing-Cost). SAPE-C integrates the cost modeling software SEER-H (System Estimation and Evaluation of Resources-Hardware) with a number of systems analysis tools and enables large design tradespace exploration early in the design process. SAPE-C is used to analyze several tradespaces of the Mid-Lift-to-Drag ratio rigid entry vehicle for human Mars missions. Key findings include quantifying the impacts of payload, vehicle length, and main engine specific impulse on the overall cost of the vehicle, and how the payload per lander and number of landers affects the cost of a campaign to Mars.

Paul D Friz↗

Towards a Multi-Variable Parametric Cost Model for Ground and Space Telescopes

Parametric cost models can be used by designers and project managers to perform relative cost comparisons between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. This paper hypothesizes a single model, based on published models and engineering intuition, for both ground and space telescopes: OTA Cost approximately (X) D(exp (1.75 +/- 0.05)) lambda(exp(-0.5 +/- 0.25) T(exp -0.25) e (exp (-0.04)Y). Specific findings include: space telescopes cost 50X to 100X more ground telescopes; diameter is the most important CER; cost is reduced by approximately 50% every 20 years (presumably because of technology advance and process improvements); and, for space telescopes, cost associated with wavelength performance is balanced by cost associated with operating temperature. Finally, duplication only reduces cost for the manufacture of identical systems (i.e. multiple aperture sparse arrays or interferometers). And, while duplication does reduce the cost of manufacturing the mirrors of segmented primary mirror, this cost savings does not appear to manifest itself in the final primary mirror assembly (presumably because the structure for a segmented mirror is more complicated than for a monolithic mirror).

Space Mirror Technology↗

Continuously Improving Parametric Modeling with Historical Data on the ICESat-2 Mission

This paper delves into the details of the Joint Confidence Level (JCL) process performed for the Ice, Cloud, and Land Elevation Satellite (ICESat)-2 mission and how past performance was incorporated into subsequent JCL models to enable the project to continuously analyze potential slips to their launch readiness date (LRD). One year prior to the mission Preliminary Review (mPDR), the JCL model development process began. The first model was well received at the mPDR, held on October 10, 2012, and the input received by the Standing Review Board was incorporated into the model for the official data drop for key decision point (KDP)-C. The 70% JCL results of the October 2012 mPDR model forecast an LRD of February 2017 and associated cost of $830M. This result in 2012 immediately highlighted potential challenges with the project-planned LRD of July 2016. The year following the mPDR, the project had sustained a oneyear slip in the LRD due to problematic systems engineering requirement issues which impacted all project subsystems. This slip moved the project planned LRD from July 2016 to July 2017, an additional 5 months beyond the 2012 model’s 70% JCL result for the LRD of February 2017. As the project was quickly approaching the mission Critical Design Review (mCDR), the need for reliable JCL results increased significantly. The project held discussions on the JCL modeling process and focused on the input uncertainty distributions. Specifically, to identify the uncertainty distributions that the 2012 mPDR model would have needed to produce a 70% LRD result of July 2017. This led the project to compare multiple uncertainty distributions, and ultimately spurred the project to utilize uncertainty distributions that incorporated project past performance and historical data to forecast potential LRD slips. The revised results, created in 2014 and utilizing the new uncertainty distributions, showed that with 70% confidence, the ICESat-2 mission would launch in August 2018 with a cost of $1,044M. Today, ICESat-2 is scheduled to launch on September 15, 2018 with a project management (PM) agreement value of $1,056M. This illustrates how a JCL model can be continuously improved to produce valuable results for a project, even in cases of LRD delays. The primary reason for the ICESat-2 LRD delay is due to a laser failure on the primary instrument. Laser failure was one of the highest risk and uncertainty drivers within the JCL model. The project placed the most risk in this area of the model, and the model further identified the laser as the top risk driver and contributor to the LRD result. This further illustrates how a JCL can be used to predict and quantify possible issues on new technology missions.

Krygiel, Joseph↗

Orbital transfer rocket engine technology: Advanced engine study

An advanced LOX/LH2 engine study for the use of NASA and vehicle prime contractors in developing concepts for manned missions to the Moon, Mars, and Phobos is documented. Parametric design data was obtained at five engine thrusts from 7.5K lbf to 50K lbf. Also, a separate task evaluated engine throttling over a 20:1 range and operation at a mixture ratio of 12 plus or minus 1 versus the 6 plus or minus 1 nominal. Cost data was also generated for DDT&E, first unit production, and factors in other life cycle costs. The major limitation of the study was lack of contact with vehicle prime contractors to resolve the issues in vehicle/engine interfaces. The baseline Aerojet dual propellant expander cycle was shown capable of meeting all performance requirements with an expected long operational life due to the high thermal margins. The basic engine design readily accommodated the 20:1 throttling requirement and operation up to a mixture ratio of 10 without change. By using platinum for baffled injector construction the increased thermal margin allowed operation up to mixture ratio 13. An initial engine modeling with an Aerojet transient simulation code (named MLETS) indicates stable engine operation with the baseline control system. A throttle ratio of 4 to 5 seconds from 10 percent to 100 percent thrust is also predicted. Performance predictions are 483.1 sec at 7.5K lbf, 487.3 sec at 20K lbf, and 485.2 sec at 50K lbf with a mixture ratio of 6 and an area ratio of 1200. Engine envelopes varied from 120 in. length/53 in. exit diameter at 7.5K lbf to 305 in. length/136 in. exit diameter at 50 K lbf. Packaging will be an important consideration. Continued work is recommended to include more vehicle prime contractor/engine contractor joint assessment of the interface issues.

Hayden, Warren R.↗

Investigation of Injector Slot Geometry on Curved-Diffuser Aerodynamic Performance

The Compressor Branch vision is to be recognized as world-class leaders in research for fluid mechanics of compressors. Its mission is to conduct research and develop technology to advance the state of the art of compressors and transfer new technology to U.S. industries. Maintain partnerships with U.S. industries, universities, and other government organizations. Maintain a balance between customers focused and long range research. Flow control comprises enabling technologies to meet compression system performance requirements driven by emissions and fuel reduction goals (e.g., in UEET), missions (e.g., access-to-space), aerodynamically aggressive vehicle configurations (e.g., UAV and future blended wing body configurations with highly distorted inlets), and cost goals (e.g., in VAATE). The compression system requirements include increased efficiency, power-to-weight, and adaptability (i.e., robustness in terms of wide operability, distortion tolerance, and engine system health and reliability). The compressor flow control task comprises efforts to develop, demonstrate, and transfer adaptive flow control technology to industry to increase aerodynamic loading at current blade row loss levels, to enable adaptive1 y wide operability, and to develop plant models for adaptive compression systems. In this context, flow control is the controlled modification of a flow field by a deliberate means beyond the natural (uncontrolled) shaping of the solid surfaces that define the principal flow path. The objective of the compressor flow control task is to develop and apply techniques that control circulation, aerodynamic blockage, and entropy production in order to enhance the performance and operability of compression systems for advanced aero-propulsion applications. This summer I would be working with a curved-diffuser because it simulates what happens with flow in the stator blades in the compressor. With this experiment I will be doing some data analysis and parametric study of the injector slot geometries to get the best aerodynamic performance of it. This includes some data reduction, redesign and fast prototyping of the injector nozzle.

Silva, Odlanier↗

Hybrid Propulsion Technology Program

Future launch systems of the United States will require improvements in booster safety, reliability, and cost. In order to increase payload capabilities, performance improvements are also desirable. The hybrid rocket motor (HRM) offers the potential for improvements in all of these areas. The designs are presented for two sizes of hybrid boosters, a large 4.57 m (180 in.) diameter booster duplicating the Advanced Solid Rocket Motor (ASRM) vacuum thrust-time profile and smaller 2.44 m (96 in.), one-quater thrust level booster. The large booster would be used in tandem, while eight small boosters would be used to achieve the same total thrust. These preliminary designs were generated as part of the NASA Hybrid Propulsion Technology Program. This program is the first phase of an eventual three-phaes program culminating in the demonstration of a large subscale engine. The initial trade and sizing studies resulted in preferred motor diameters, operating pressures, nozzle geometry, and fuel grain systems for both the large and small boosters. The data were then used for specific performance predictions in terms of payload and the definition and selection of the requirements for the major components: the oxidizer feed system, nozzle, and thrust vector system. All of the parametric studies were performed using realistic fuel regression models based upon specific experimental data.

Jensen, G. E.↗

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗