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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Environmental Signatures for Habitability: What to Measure and How to Rank the Habitability Potential of Mars

The environmental signatures for habitability are not necessarily biosignatures, even though on Earth, they are definitive proof of habitability. It is the constant overprint of the chemical signatures of life that makes it difficult to recognize the chemical and physical properties of a potentially habitable environment as distinct from an inhabited one. Mars Science Laboratory (MSL) will soon embark on a mission to Mars to assess its past or present habitability, so it is useful to examine how we measure habitability on Earth and prepare for how that approach may differ for Mars. This exercise includes: (a) articulation of fundamental assumptions about habitability, (b) an inventory of factors that affect habitability, (c) development of metrics, measurement approach and implementation, and (d) a new classification scheme for planetary habitability that goes beyond the binary "yes" or "no." There may be dozens of factors that affect habitability and they can be weighted as a function of specific environment. However a robotic, in situ investigation even on Earth has constraints that prevent the measurement of every environmental factor, so metrics must be reduced to the most relevant subset, given available time, cost, technical feasibility and scientific importance. Many of the factors could be measured with a combination of orbital data and the MSL payload. We propose that, at a minimum, a designation of high habitability potential requires the following conditions be met: (a) thermally stable with respect to extremes and frequency of fluctuation, (b) has more than one energy source, (c) sufficient chemical diversity to make compounds with covalent and hydrogen bonding, (d) can moderate ionizing radiation enough to allow a stable or evolving pool of organic molecules, (e) must have water or other high quality polar solvent, (f) must be able to renew chemical resources (e.g., plate tectonics, volcanism or something else we haven't envisioned). A measurement approach we have taken to measure habitability on Earth is : 1. Study remote sensing data, maps, etc. 2. Decide how big an area to measure. 3. Determine the spatial sampling rate. 4. Determine the temporal sampling rate. 5. Determine the order of measurements 6. Decide where to begin measurements 7. Select locations at field site and proceed While science drives each of the steps, there are additional constraints, e.g., technical, time, cost, safety (risk). This approach is also executable on Mars. Measurement of past habitability is more challenging both for Earth and Mars where access to the past means subsurface access and confrontation with unknowns about preservation of the martian past. Some environments preserve evidence of past habitability better than others, and this is where selection of the landing site to maximize the preservation potential of habitability indicators will be key. Mars presents an opportunity to discover transitional states between habitable or not, and we offer a ranking scale for planetary habitability with Mars as the second test subject: CLASS ONE Uninhabitable and likely has never been so CLASS TWO Has a high potential but no confirmed observation of life (as defined above) CLASS THREE Inhabited (we find life) 3-A Globally inhabited 3-B Primitive life; early in its evolution, but not yet globally established 3-C Exists only in refugia -- planet heading toward class four CLASS FOUR Post-habitable (there once was life, but now it's gone) MSL provides an opportunity to carefully investigate the habitability of at least one site on Mars and it will reveal much about the possible states of planetary habitability

Conrad, Pamela G.↗
NASA NTRS2011

Density Weighted FDF Equations for Simulations of Turbulent Reacting Flows

In this report, we briefly revisit the formulation of density weighted filtered density function (DW-FDF) for large eddy simulation (LES) of turbulent reacting flows, which was proposed by Jaberi et al. (Jaberi, F.A., Colucci, P.J., James, S., Givi, P. and Pope, S.B., Filtered mass density function for Large-eddy simulation of turbulent reacting flows, J. Fluid Mech., vol. 401, pp. 85-121, 1999). At first, we proceed the traditional derivation of the DW-FDF equations by using the fine grained probability density function (FG-PDF), then we explore another way of constructing the DW-FDF equations by starting directly from the compressible Navier-Stokes equations. We observe that the terms which are unclosed in the traditional DW-FDF equations are now closed in the newly constructed DW-FDF equations. This significant difference and its practical impact on the computational simulations may deserve further studies.

Shih, Tsan-Hsing↗
NASA NTRS2018

An Efficient Inverse Finite Element Method for Shape and Stress Sensing of Laminated Composite and Sandwich Plates and Shells

The inverse Finite Element Method (iFEM) is a revolutionary methodology for real-time reconstruction of full-field structural displacements and stresses in structures that are instrumented with strain sensors. This inverse problem is commonly referred to as shape and stress sensing, which is well-recognized as an enabling technology for structural health monitoring systems. In this study, an improved iFEM formulation is proposed for shape and stress sensing of laminated composite and sandwich plates and shells. The formulation includes the kinematics of a shear deformation plate theory known as Refined Zigzag Theory (RZT) as its baseline. The present iFEM formulation is based upon the minimization of a weighted-least-squares functional that uses the complete set of section strains of RZT. The improved iFEM methodology is applicable for shape and stress sensing of thin and moderately thick plate and shell structures involving a relatively small number of strain gauges. The main advantage of the current formulation is that highly accurate through-the-thickness distributions of displacements, strains, and stresses are attainable using an element based on simple C0-continuous displacement interpolation functions. A three-node inverseshell element, named i3-RZT, is developed. Two example problems are examined in detail: (1) a simply supported rectangular laminated composite plate and (2) a wedge structure with a hole near one of the clamped ends. For both problems, the experimental strain data are generated numerically by the direct finite element analysis using high-fidelity discretizations. These strains are then regarded as the experimental strains obtained from surface mounted strain gauges or embedded fiber Bragg grating (FBG) sensors. The numerical results demonstrate the superior capability and potential applicability of the i3- RZT/iFEM methodology for performing accurate shape and stress sensing of complex composite structures.

Kefal, Adnan↗
NASA NTRSDate not supplied

Aero-Propulsive Modeling for eVTOL Aircraft Using Wind Tunnel Testing with Multisine Inputs

A novel approach for modeling the aero-propulsive characteristics of an electric vertical takeoff and landing (eVTOL) aircraft was developed and demonstrated in wind tunnel testing. The approach was applied to the NASA LA-8 tandem tilt-wing eVTOL aircraft, using an efficient, hybrid experiment design composed of a static I-optimal response surface design for slowly-varying test variables, and dynamic orthogonal phase-optimized multisine excitations for the control surfaces and electric propulsors. Both the static and dynamic experiment designs were executed simultaneously to collect informative data for model identification. Statistically-weighted multivariate orthogonal function modeling was used to combine local modeling results computed in the frequency domain using data collected with dynamic excitations operating on the control effectors to form an aggregate aero-propulsive model. The final identified model exhibited good predictive capability when compared to validation data acquired separately from the data used to develop the model. The required test time using these new techniques was reduced by at least a factor of five compared to previous static wind tunnel testing for the LA-8 aircraft, while providing more informative data, greater parameterization flexibility, and high-quality models.

system identification↗
NASA NTRS2022

Recommendations on the Use of Commercial-Off-The-Shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) Parts for NASA Missions - Phase II

This assessment had two Phases. Phase I captured NASA Centers’ current practices for commercial-off-the-shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) parts 1 used in spaceflight systems and ground support equipment (available at https://ntrs.nasa.gov/citations/20205011579) [ref. 1]. The Phase II report provides guidance for selecting and using COTS parts in NASA missions. The approaches proposed in this report differ from current agency practices. This top-level executive summary touches on these new approaches for using COTS parts but does not provide the detailed information that is critical in understanding the rationale behind these new approaches. Readers will need to read the entire report to gain full understanding and effectively use the recommendations herein. NASA’s historical approach to selecting and applying parts has been to define certain parts, primarily specific classes of military specification (MIL-SPEC) parts, as “standard”, leaving all others, including COTS parts, as nonstandard. Standard parts typically are used without further testing (“use-as-is”). Nonstandard parts are subjected to initial screening and subsequent lot acceptance testing of representative samples from each procured lot per MIL-SPEC or similar requirements. Decades later, top-tier commercial part manufacturers have evolved significant manufacturing, statistical control, and technological improvements that can now provide parts as reliable or more reliable than MIL-SPEC parts, when used within their datasheet limits. Concurrently, the space science and exploration community’s needs demand technological advances unavailable with MIL-SPEC parts. This ongoing change necessitates using COTS parts for space missions. Properly selected COTS parts in appropriate applications can offer performance and supply availability advantages compared to MIL-SPEC parts. Their utility and demonstrated reliability result from large volumes and automated production and testing processes. However, careful review and a thorough understanding of their specifications (i.e., datasheet limitations) is needed, and verifying that manufacturer specifications and reliability meet space hardware application needs are necessary. This report recommends MIL-SPEC screening and non-radiation-related lot acceptance testing be reduced or eliminated in cases where evidence of sufficient quality and reliability exists for COTS parts. The extent of NASA's insight into COTS manufacturers and the amount and nature of the needed evidence will differ by mission and will likely be driven by a mission's resources and associated risk posture. To facilitate this goal, two new terminologies have been defined and described: “Industry Leading Parts Manufacturer (ILPM)” and “Established COTS parts.” An ILPM is a COTS manufacturer that produces high quality and reliable parts. Some parts produced by ILPMs, defined as Established COTS parts, do not need any additional MIL-SPEC or NASA screening and lot acceptance testing to be used in space applications. This report provides guidance for selecting, procuring, and applying COTS parts and for performing part-, board-, and system-level COTS parts verification. The recommendation to select Established COTS parts from ILPMs will assure those COTS parts will have comparable quality to corresponding MIL-SPEC parts. Selecting, applying, and verifying Established COTS parts from ILPMs requires a holistic team approach, engaging parts engineers, circuit designers, quality, reliability, and systems engineers, procurement specialists, radiation specialists, avionics leads, and program/project managers. A mission-specific approach tailored to a project’s Mission, Environment, Applications and Lifetime (MEAL) [ref. 2] requirements should be developed and approved by program/project managers. Any associated risks should be clearly identified, quantified, mitigated, and/or accepted. Different approaches are recommended according to program/project Risk Classes A, B, C, and D [ref. 3] and human-rated missions [ref. 4]: 1. Recommend Classes A and B and human-rated missions consider a “MIL-SPEC parts- based design” approach. ”MIL-SPEC parts-based design” approach is one in which most parts are MIL-SPEC parts and Established COTS parts from ILPMs are used only when an equivalent MIL-SPEC part does not meet functional or size, weight, and power (SWaP) or performance requirements, or is not available. 2. Recommend Classes D and Sub-D missions consider a “System of COTS” approach. “System of COTS” approach is one which most parts are Established COTS parts from ILPMs. 3. Recommend Class C missions determine which approach is the best for their projects; that is, use either a “MIL-SPEC parts-based design” approach, “System of COTS” approach, or a combined approach utilizing elements of both. This report intends to provide guidance in using COTS parts for NASA missions with risk classifications of A through D and human-rated missions; but it does not address the costs of using COTS parts. Costs of using COTS parts in different NASA mission classes can vary significantly even if the same parts are used in different risk postures, due to differing verification levels needed. The guidance does not distinguish between critical or non-critical systems, and a given project will need to apply the appropriate guidance based on their risk posture. The intended audience of this report are NASA personnel and commercial practitioners who support NASA’s spaceflight missions, including spaceflight program or project managers, parts engineers, parts manufacturers, radiation engineers, avionics engineers, system engineers, circuit design engineers, reliability engineers, safety and mission assurance (SMA) personnel, and parts procurement specialists. The NEPP Program will perform a pathfinder study to explore implementing the guidance in this NESC report. An ILPM verification process is not the same as conventional vendor qualification processes performed according to military standards and specifications. This NESC report intends to provide guidance in utilizing available parts data from ILPM manufacturers for parts assurance assessments needed for NASA missions. The report also captured the current practices from DoD and Federal Aviation Administration (FAA) in Section 10. Note each DoD and FAA report was provided by the corresponding agencies regarding their practices, which are independent from the NESC recommendations in the report.

Commercial-Off-The-Shelf↗
NASA NTRS2026

A Modular Conjugate Heat Transfer Optimization Framework for Thermal Management of Electric Aircraft

Conjugate heat transfer (CHT) analysis and optimization is a powerful method for improving thermal management, as it simultaneously resolves the temperature distribution in both fluid and solid domains. This paper presents a modular, discrete adjoint-based CHT optimization capability integrated within the OpenMDAO/MPhys framework. A unique feature of the proposed framework is its flexibility to extend to multidisciplinary optimization, including aero-structural-thermal applications. The fluid domain is modeled using a finite-volume Computational Fluid Dynamics (CFD) solver, and the solid domain with a conduction heat transfer solver. A mixed Neumann-Dirichlet boundary condition is developed to enable full submersion of the solid geometry within the fluid domain, while ensuring consistent temperature and heat flux coupling at the CHT interface. Gradient-based optimization is performed; the gradients are efficiently computed using the discrete adjoint solvers implemented in DAFoam. To demonstrate the method, this paper considers two cases related to electric aircraft thermal management: a U-bend heat exchanger and an actively cooled battery pack. The U-bend case aims to minimize pressure loss while maximizing heat flux by changing the pipe geometry. The optimized design reduces pressure loss by 52.7% and increases total heat flux by 2.3%. In the battery pack case, a 3-by-3 cell configuration is cooled by ambient airflow, with constant heat generation prescribed in the cells. The battery casing shape serves as the design variable, and the objective function is a weighted sum of pressure loss and pack weight, subject to a maximum temperature constraint. The optimized design achieves a 44.6% reduction in pressure loss and a 1.5% reduction in weight, while satisfying the thermal constraint. To ensure the reliability of the optimized designs, this study validates coarse-mesh, steady-state predictions against fine-mesh unsteady simulations, demonstrating consistency within acceptable errors. This work demonstrates the potential of the developed framework to enable rapid, high-fidelity design of thermal management systems for electric aircraft.

heat transfer↗
DOE OSTI2024

The Reservoir Temperature Estimator (RTEst): A multicomponent geothermometry tool

The Reservoir Temperature Estimator (RTEst) is a multicomponent geothermometry tool for estimating reservoir geochemical parameters including reservoir temperature, CO 2 fugacity, mass of water lost or gained, and a reaction factor. It estimates these parameters and their associated uncertainties by minimizing an objective function that is the weighted sum of squares of the saturation indices of a user-selected set of minerals believed to be equilibrated with the reservoir fluid. RTEst accomplishes these estimates by combining the geochemical modeling capabilities of The Geochemist’s Workbench® with the optimization/parameter estimation resources of PEST®. An included interface aids the user in selecting plausible mineral phases to comprise the objective function and calculates their weighting factors. The working principles of RTEst are described and its efficacy is illustrated by presenting results of its application to various geothermal fields with known conditions. These examples show RTEst can account for the alteration of ascending reservoir fluid by mineral (calcite) re-equilibration with changes in temperature, reconstruct waters with CO 2 loss, correct for the deficit of water and other volatiles (CO 2,gas , H 2 S gas ) from boiling, and determine the amount of mixing of thermal and non-thermal waters. RTEst can use data with basis species below detection limit, missing, or unreliable either by assuming equilibrium with a controlling mineral (fixed-analyte method) or by treating the analyte concentration as an optimization parameter. The inverse of variance weighting method included in RTEst provides more representative results than either the normalization or unit weighting methods. Finally, the ability of RTEst to calculate reservoir temperatures, gas fugacity, and mixing fractions demonstrates its usefulness as a tool for evaluating geothermal systems.

15 GEOTHERMAL ENERGY↗
NASA NTRS1991

Neural networks: What non-linearity to choose

Neural networks are now one of the most successful learning formalisms. Neurons transform inputs (x(sub 1),...,x(sub n)) into an output f(w(sub 1)x(sub 1) + ... + w(sub n)x(sub n)), where f is a non-linear function and w, are adjustable weights. What f to choose? Usually the logistic function is chosen, but sometimes the use of different functions improves the practical efficiency of the network. The problem of choosing f as a mathematical optimization problem is formulated and solved under different optimality criteria. As a result, a list of functions f that are optimal under these criteria are determined. This list includes both the functions that were empirically proved to be the best for some problems, and some new functions that may be worth trying.

Kreinovich, Vladik YA.↗
NASA NTRS1998

Application of Least Mean Square Algorithms to Spacecraft Vibration Compensation

This paper describes the application of the Least Mean Square (LMS) algorithm in tandem with the Filtered-X Least Mean Square algorithm for controlling a science instrument's line-of-sight pointing. Pointing error is caused by a periodic disturbance and spacecraft vibration. A least mean square algorithm is used on-orbit to produce the transfer function between the instrument's servo-mechanism and error sensor. The result is a set of adaptive transversal filter weights tuned to the transfer function. The Filtered-X LMS algorithm, which is an extension of the LMS, tunes a set of transversal filter weights to the transfer function between the disturbance source and the servo-mechanism's actuation signal. The servo-mechanism's resulting actuation counters the disturbance response and thus maintains accurate science instrumental pointing. A simulation model of the Upper Atmosphere Research Satellite is used to demonstrate the algorithms.

Woodard , Stanley E.↗
NASA NTRS1990

Gaussian windows: A tool for exploring multivariate data

Presented here is a method for interactively exploring a large set of quantitative multivariate data, in order to estimate the shape of the underlying density function. It is assumed that the density function is more or less smooth, but no other specific assumptions are made concerning its structure. The local structure of the data in a given region may be examined by viewing the data through a Gaussian window, whose location and shape are chosen by the user. A Gaussian window is defined by giving each data point a weight based on a multivariate Gaussian function. The weighted sample mean and sample covariance matrix are then computed, using the weights attached to the data points. These quantities are used to compute an estimate of the shape of the density function in the window region. The local structure of the data is described by a method similar to the method of principal components. By taking many such local views of the data, we can form an idea of the structure of the data set. The method is applicable in any number of dimensions. The method can be used to find and describe simple structural features such as peaks, valleys, and saddle points in the density function, and also extended structures in higher dimensions. With some practice, we can apply our geometrical intuition to these structural features in any number of dimensions, so that we can think about and describe the structure of the data. Since the computations involved are relatively simple, the method can easily be implemented on a small computer.

Jaeckel, Louis A.↗
DOE OSTI2024

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗
DOE OSTI2022

Cumulant methods for electron-phonon problems. I. Perturbative expansions

Here in this work, we investigate the ability of the cumulant expansion (CE) to capture one-particle spectral information in electron-phonon coupled systems at both zero and finite temperatures. In particular, we present a comprehensive study of the second- and fourth-order CEs for the one-dimensional Holstein model as compared with numerically exact methods. We investigate both finite sized systems as well as the approach to the thermodynamic limit, drawing distinctions, and connections between the behavior of systems in and away from the thermodynamic limit that enable a greater understanding of the ability of the CE to capture real-frequency information across the full range of wave vectors. We find that for zero electronic momentum, the spectral function is well described by the second-order CE at low and high temperatures. However, for nonzero electronic momenta, the CE is only accurate at high temperature. We analyze the fourth-order cumulant and find that while it improves the description of the short-time dynamics encoded in the one-particle Green's function, it can introduce divergences in the time domain as well as unphysical negative spectral weight in the spectral function. When well-behaved, the fourth-order CE does provide notable accurate corrections to the second-order CE. Finally, we use our results to comment on the use of the CE as a tool for calculating transport behavior in the realistic ab initio modeling of materials.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Reliability-Based Design Optimization of a Composite Airframe Component

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Patnaik, Surya N.↗
NASA NTRS1985

Quantitative Alterations in the Function of Bone Forming Cells Due to Reduced Weight Bearing

Rats subjected to spaceflight or suspended in a non-weight bearing position for 2 to 3 weeks, show a significant reduction in new bone formation. This reduction is associated with a decrease in akaline phosphatase activity in the differentiated osteoblast population. Those cells in the siaphyseal region of bone are more affected than the same cell type in metaphyseal bone. Measurements of alkaline phosphate activity in specific regions of bone, and the autoradiographic localization of H(3) proline in bone forming areas are described. Concomitant with decreased bone matrix synthesis, the osteoblast population also demonstrate changes in the Golgi/lysosomal complex as a result of whole animal suspension. Morphometric techniques are being applied for quantitation of the lysosomal population and the percentage of lysosomal or Golgi bodies containing acid phosphatase activity.

Doty, S. B.↗
NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗
NASA NTRS1986

Atmospheric solar heating rate in the water vapor bands

The total absorption of solar radiation by water vapor in clear atmospheres is parameterized as a simple function of the scaled water vapor amount. For applications to cloudy and hazy atmospheres, the flux-weighted k-distribution functions are computed for individual absorption bands and for the total near-infrared region. The parameterization is based upon monochromatic calculations and follows essentially the scaling approximation of Chou and Arking, but the effect of temperature variation with height is taken into account in order to enhance the accuracy. Furthermore, the spectral range is extended to cover the two weak bands centered at 0.72 and 0.82 micron. Comparisons with monochromatic calculations show that the atmospheric heating rate and the surface radiation can be accurately computed from the parameterization. Comparisons are also made with other parameterizations. It is found that the absorption of solar radiation can be computed reasonably well using the Goody band model and the Curtis-Godson approximation.

Chou, Ming-Dah↗
NASA NTRS1971

Advanced Extravehicular Protective Systems (AEPS) study

A description is given of life support subsystem concepts for advanced extravehicular protective systems (AEPS) intended for use on future orbital, lunar surface, and Mars surface missions in the late 1970's and 1980's. Primary interest was centered around the thermal control and carbon dioxide control subsystems because they offer the greatest potential for total weight savings. Emphasis was placed on the generation of regenerable subsystem concepts; however, partially regenerable and expendable concepts were also considered. Previously conceived and developed subsystem concepts were included in the study. Concepts were evaluated on the basis of subsystem weight and volume, and subsystem contribution to parent vehicle weight and volume, which included spares, regeneration equipment, expendables, expandables storage penalty, power penalty, and process heating or cooling penalty. Results are presented showing total weight and volume penalty as a function of total mission extravehicular activity (EVA) hours, and showing EVA weight and volume as a function of EVA duration. Subsystem concepts are recommended for each life support function, and secondary concepts which should be developed are also identified.

Williams, J. L.↗
NASA NTRS2000

Nontangent, Developed Contour Bulkheads for a Single-Stage Launch Vehicle

Dry weights for single-stage launch vehicles that incorporate nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1.414 aspect ratio ellipsoidal bulkheads. Weights, volumes, and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weights of vehicles that incorporate the optimized bulkheads are predicted using a vehicle weights and sizing code. Two optimization approaches are employed. A structural-level method, where the vehicle's three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of4365 lb (2.2 %) from the 200,679-lb baseline vehicle dry weight. In the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. For the vehicle-level analysis, modified bulkhead designs are analyzed and incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle-level analysis predicts a dry weight reduction of 5129 lb, a 2.6% reduction from the baseline weight. Based on these results, nontangent, developed contour bulkheads may provide substantial weight savings for single stage vehicles.

Wu, K. Chauncey↗