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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Error-Based Design Space Windowing

Windowing of design space is considered in order to reduce the bias errors due to low-order polynomial response surfaces (RS). Standard design space windowing (DSW) uses a region of interest by setting a requirement on response level and checks it by a global RS predictions over the design space. This approach, however, is vulnerable since RS modeling errors may lead to the wrong region to zoom on. The approach is modified by introducing an eigenvalue error measure based on point-to-point mean squared error criterion. Two examples are presented to demonstrate the benefit of the error-based DSW.

Papila, Melih↗
DOE OSTI2013

Optimization of stabilized leachate treatment using ozone/persulfate in the advanced oxidation process

Highlights: ► Ozone and persulfate reagent (O{sub 3}/S{sub 2}O{sub 8}{sup 2-}) was used to treat stabilized leachate. ► Central composite design (CCD) with response surface methodology (RSM) was applied. ► Operating variables including ozone and persulfate dosage, pH variance, and reaction time. ► Optimum removal of COD, color, and NH{sub 3}–N was 72%, 96%, and 76%, respectively. ► A good value of ozone consumption (OC) obtained with 0.60 (kg O{sub 3}/kg COD). - Abstract: The objective of this study was to investigate the performance of employing persulfate reagent in the advanced oxidation of ozone to treat stabilized landfill leachate in an ozone reactor. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as ozone and persulfate dosages, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following four responses proved to be significant with very low probabilities (<0.0001): COD, color, NH{sub 3}–N, and ozone consumption (OC). The obtained optimum conditions included a reaction time of 210 min, 30 g/m{sup 3} ozone, 1 g/1 g COD{sub 0}/S{sub 2}O{sub 8}{sup 2-} ratio, and pH 10. The experimental results were corresponded well with predicted models (COD, color, and NH{sub 3}–N removal rates of 72%, 96%, and 76%, respectively, and 0.60 (kg O{sub 3}/kg COD OC). The results obtained in the stabilized leachate treatment were compared with those from other treatment processes, such as ozone only and persulfate S{sub 2}O{sub 8}{sup 2-} only, to evaluate its effectiveness. The combined method (i.e., O{sub 3}/S{sub 2}O{sub 8}{sup 2-}) achieved higher removal efficiencies for COD, color, and NH{sub 3}–N compared with other studied applications. Furthermore, the new method is more efficient than ozone/Fenton in advanced oxidation process in the treatment of the same studied leachate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2010

Advanced Response Surface Modeling of Ares I Roll Control Jet Aerodynamic Interactions

The Ares I rocket uses roll control jets. These jets have aerodynamic implications as they impinge on the surface and protuberances of the vehicle. The jet interaction on the body can cause an amplification or a reduction of the rolling moment produced by the jet itself, either increasing the jet effectiveness or creating an adverse effect. A design of experiments test was planned and carried out using computation fluid dynamics, and a subsequent response surface analysis ensued on the available data to characterize the jet interaction across the ascent portion of the Ares I flight envelope. Four response surface schemes were compared including a single response surface covering the entire design space, separate sector responses that did not overlap, continuously overlapping surfaces, and recursive weighted response surfaces. These surfaces were evaluated on traditional statistical metrics as well as visual inspection. Validation of the recursive weighted response surface was performed using additionally available data at off-design point locations.

Favaregh, Noah M.↗
NASA NTRS1999

Development of Response Surface Models for Rapid Analysis & Multidisciplinary Optimization of Launch Vehicle Design Concepts

Multdisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO. An alternative has been to utilize response surface methodology (RSM) to obtain polynomial models that approximate the functional relationships between performance characteristics and design variables. These approximation models, called response surface models, are then used to integrate the disciplines using mathematical programming methods for efficient system level design analysis, MDO and fast sensitivity simulations. A second-order response surface model of the form given has been commonly used in RSM since in many cases it can provide an adequate approximation especially if the region of interest is sufficiently limited.

Unal, Resit↗
NASA NTRS2004

Applications of Response Surface-Based Methods to Noise Analysis in the Conceptual Design of Revolutionary Aircraft

Due to the growing problem of noise in today's air transportation system, there have arisen needs to incorporate noise considerations in the conceptual design of revolutionary aircraft. Through the use of response surfaces, complex noise models may be converted into polynomial equations for rapid and simplified evaluation. This conversion allows many of the commonly used response surface-based trade space exploration methods to be applied to noise analysis. This methodology is demonstrated using a noise model of a notional 300 passenger Blended-Wing-Body (BWB) transport. Response surfaces are created relating source noise levels of the BWB vehicle to its corresponding FAR-36 certification noise levels and the resulting trade space is explored. Methods demonstrated include: single point analysis, parametric study, an optimization technique for inverse analysis, sensitivity studies, and probabilistic analysis. Extended applications of response surface-based methods in noise analysis are also discussed.

Hill, Geoffrey A.↗
NASA NTRS1997

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

Simpson, Timothy W.↗
NASA NTRS1997

On the Use of Statistics in Design and the Implications for Deterministic Computer Experiments

Perhaps the most prevalent use of statistics in engineering design is through Taguchi's parameter and robust design -- using orthogonal arrays to compute signal-to-noise ratios in a process of design improvement. In our view, however, there is an equally exciting use of statistics in design that could become just as prevalent: it is the concept of metamodeling whereby statistical models are built to approximate detailed computer analysis codes. Although computers continue to get faster, analysis codes always seem to keep pace so that their computational time remains non-trivial. Through metamodeling, approximations of these codes are built that are orders of magnitude cheaper to run. These metamodels can then be linked to optimization routines for fast analysis, or they can serve as a bridge for integrating analysis codes across different domains. In this paper we first review metamodeling techniques that encompass design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We discuss their existing applications in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of metamodeling techniques in given situations and how common pitfalls can be avoided.

Simpson, Timothy W.↗
NASA NTRS2001

A Rapid Aerodynamic Design Procedure Based on Artificial Neural Networks

An aerodynamic design procedure that uses neural networks to model the functional behavior of the objective function in design space has been developed. This method incorporates several improvements to an earlier method that employed a strategy called parameter-based partitioning of the design space in order to reduce the computational costs associated with design optimization. As with the earlier method, the current method uses a sequence of response surfaces to traverse the design space in search of the optimal solution. The new method yields significant reductions in computational costs by using composite response surfaces with better generalization capabilities and by exploiting synergies between the optimization method and the simulation codes used to generate the training data. These reductions in design optimization costs are demonstrated for a turbine airfoil design study where a generic shape is evolved into an optimal airfoil.

Rai, Man Mohan↗
NASA NTRS2003

Method for Constructing Composite Response Surfaces by Combining Neural Networks with other Interpolation or Estimation Techniques

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

Rai, Man Mohan↗
NASA NTRSDate not supplied

Recommended Crew Systems Capabilities for a 30 to 90 Day Four-Crew Lunar Surface Mission

For any given surface mission duration, there exists a set of surface capabilities necessary to sustain a four-person crew for the length of time the crew is on the surface. Identifying these capabilities is important to mission planners and spacecraft design engineers responsible for lunar surface habitation elements, who need to know which systems and capabilities must be prioritized for the vehicles they are designing. However, simply identifying the surface capabilities does not necessarily equal a viable surface configuration. These capabilities may or may not satisfy stakeholder expectations or even permit completion of mission objectives. Lunar lander cargo mass constraints are a powerful forcing function that requires significant efforts to reduce the mass of all surface elements, including those supporting crew habitation. The required capabilities do increase as a function of mission duration, but it is a nonlinear growth. There are key points in mission duration, beyond which certain additional capabilities are needed. This forms bands of capability between each point. Within a given band, the same functional capabilities are needed, and the only scaling is that associated with daily consumables. The next higher band requires additional capabilities. This paper will focus on those capabilities needed for missions of 30-90 days. It should be noted that there are some uncertainties interpreting NASA requirements that require capabilities after a certain number of days, as typically this refers to number of days in space, not number of days on the lunar surface. Depending on transportation architecture, the number of days between Earth launch and lunar surface landing may vary, therefore impacting when certain required capabilities are implemented. However, activities to prepare humans for missions to Mars and commercial interest in lunar development may drive progressive increases in surface duration. Missions up to 30 days are expected to follow the initial 6.5-day surface missions and there may be commercial interest in extending to even greater durations. This paper will examine the potential case of a 30-90-day surface mission duration with respect to the systems necessary to support crew living and working on the lunar surface.

Habitat↗
DOE OSTI2018

Fabrication of Biodegradable Superabsorbent Using RSM Design for Controlled Release of KNO{sub 3}

Present study envisaged the sequential experimental design approach for the development of biodegradable Gelatin-Tapoica/polyacrylamide superabsorbent. Percentage water uptake efficacy of candidate sample was optimized using Response Surface Methodology (RSM) design under microwave irradiation. Different process variables such as potassium persulphate and ammonium persulphate (KPS:APS) ratio, pH, reaction time concentration of acrylamide and N,N-methylene-bis-acrylamide (MBA) were investigated as a function of percentage swelling using sequential experimental design. Maximum liquid efficacy of 1550% was obtained at KPS:APS = 1.0:0.5; acrylamide = 7.67 × 10{sup −1} mol L{sup −1}; MBA = 1.76 × 10{sup −2} mol L{sup −1}; pH 10 and time = 110 s. The 3D crosslinked network formed was characterized using Fourier Transformation Infrared spectroscopy (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopic (SEM) techniques and thermal stability was ensured by Thermal gravimetric Analysis/Differential Thermal Analysis/Differential Thermal Gravimetric (TGA/DTA/DTG) studies. Superabsorbent synthesized could increase the moisture content in different type of soils and was found to enhance the water-holding capability of the soil upto 60 days in clayey, 40 days in sandy and 51 days in mixture of two soils under controlled conditions. Further, candidate polymer was investigated for the in-vitro controlled release of the KNO{sub 3} with diffusion exponent ‘n’ was found to be 0.4326 indicating Fickian type diffusion. Also, initial diffusion coefficient (D{sub I} = 3.49 × 10{sup −5} m{sup 2} h{sup −1}) was found to be greater than the lateral diffusion coefficient (D{sub L} = 3.76 × 10{sup −6} m{sup 2} h{sup −1}) indicated rapid release of KNO{sub 3} during initial hours with slow release afterwards. The ecofriendly nature of the synthesized polymer was also tested by conducting biodegradation studies and it was found to degrade upto 94% and 88.1% within 70 days with degradation rate of 1.34 and 1.26% per day using composting method and vermicomposting method respectively. So, the synthesized candidate polymer was found to be boon for agriculture-horticulture sector with wide applicability.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Optimal Micro-Jet Flow Control for Compact Air Vehicle Inlets

The purpose of this study on micro-jet secondary flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to optimally design micro-jet secondary flow control arrays, and to establish that the aeromechanical effects of engine face distortion can also be included in the design and optimization process. These statistical design concepts were used to investigate the design characteristics of "low mass" micro-jet array designs. The term "low mass" micro-jet may refers to fluidic jets with total (integrated) mass flow ratios between 0.10 and 1.0 percent of the engine face mass flow. Therefore, this report examines optimal micro-jet array designs for compact inlets through a Response Surface Methodology.

Anderson, Bernhard H.↗
NASA NTRS2004

Optimal Micro-Vane Flow Control for Compact Air Vehicle Inlets

The purpose of this study on micro-vane secondary flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to optimally design micro-vane secondary flow control arrays, and to establish that the aeromechanical effects of engine face distortion can also be included in the design and optimization process. These statistical design concepts were used to investigate the design characteristics of "low unit strength" micro-effector arrays. "Low unit strength" micro-effectors are micro-vanes set at very low angles-of-incidence with very long chord lengths. They were designed to influence the near wall inlet flow over an extended streamwise distance, and their advantage lies in low total pressure loss and high effectiveness in managing engine face distortion. Therefore, this report examines optimal micro-vane secondary flow control array designs for compact inlets through a Response Surface Methodology.

Anderson, Bernhard H.↗
NASA NTRS2003

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

Rais-Rohani, Masoud↗
NASA NTRSDate not supplied

Statistical Wind-Tunnel Experimentation Advancements for eVTOL Aircraft Aero-Propulsive Model Development

Compared to many conventional aircraft, electric vertical takeoff and landing (eVTOL) vehicle designs present greater aero-propulsive complexity and many interacting factors requiring development of novel testing and model development strategies. This paper describes several advances in statistically-rigorous experiment design methods for wind-tunnel testing of eVTOL aircraft enabling accurate aero-propulsive model development. The techniques are applied to a subscale tilt-rotor eVTOL aircraft configuration built at NASA Langley Research Center that has 24 independent control effectors. The general testing approach, leveraging design of experiments and response surface methodology, is outlined and followed by a detailed description of the experiment design and modeling approach employed for different phases of the wind-tunnel testing. A new approach for gravitational tare modeling is developed and validated, which reduces the required wind-tunnel test time by nearly 50%. A mostly automated trim envelope determination approach is formulated to rapidly determine the aircraft flight envelope to inform transition testing for aero-propulsive model development. Efficient powered-airframe characterization tests are conducted using a nested I-optimal design approach formulated in previous simulation-based testing. The collective wind-tunnel testing approach facilitates rapid characterization of eVTOL aircraft configurations and produces accurate aero-propulsive models that can be used in flight dynamics simulations.

design of experiments↗
DOE OSTI2015

Simplified predictive models for CO 2 sequestration performance assessment

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Hypersonic Wind Tunnel Calibration Using the Modern Design of Experiments

A calibration of a hypersonic wind tunnel has been conducted using formal experiment design techniques and response surface modeling. Data from a compact, highly efficient experiment was used to create a regression model of the pitot pressure as a function of the facility operating conditions as well as the longitudinal location within the test section. The new calibration utilized far fewer design points than prior experiments, but covered a wider range of the facility s operating envelope while revealing interactions between factors not captured in previous calibrations. A series of points chosen randomly within the design space was used to verify the accuracy of the response model. The development of the experiment design is discussed along with tactics used in the execution of the experiment to defend against systematic variation in the results. Trends in the data are illustrated, and comparisons are made to earlier findings.

Rhode, Matthew N.↗
DOE OSTI2017

Stochastic Analysis of Levee Stability Subject to Variable Seepage Conditions

© ASCE. Levee stability is highly influenced by seepage. Specifically, hydraulic conductivity distribution within a levee influences pore pressure distribution and controls the drained strength of the soil. In this study the influence of hydraulic conductivity and blanket layer thickness on failure probability is evaluated within the context of reliability analyses that also include soil strength and unit weight as random variables. First-Order Reliability Method (FORM) is used to evaluate reliability, rank random variables by importance and to obtain sensitivity of the solution to each random variable and its distribution parameters. Stability is computed using Spencer's method of slices coupled to a finite element seepage code to directly evaluate pore pressure. In addition, response surface method solutions are compared to the direct reliability solution to assess response surface accuracy. The results show that blanket layer thickness is more important than most strength parameters and that the uncertainty in hydraulic conductivity is less important to the variance in safety factor for the case of a low-permeability blanket layer. Numerical challenges caused by implementing a finite element limit-state function are discussed. Response surface methods are found to give a reasonable approximation to the direct reliability solution when the design point is between response surface fitting points.

Lanzafame, Robert↗