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At least 163 records · Page 9

Software-Engineering Process Simulation (SEPS) model

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

Lin, C. Y.↗

Series Bosch System Development

State-of-the-art (SOA) carbon dioxide (CO2) reduction technology for the International Space Station produces methane as a byproduct. This methane is subsequently vented overboard. The associated loss of hydrogen ultimately reduces the mass of oxygen that can be recovered from CO2 in a closed-loop life support system. As an alternative to SOA CO2 reduction technology, NASA is exploring a Series-Bosch system capable of reducing CO2 with hydrogen to form water and solid carbon. This results in 100% theoretical recovery of oxygen from metabolic CO2. In the past, Bosch-based technology did not trade favorably against SOA technology due to a high power demand, low reaction efficiencies, concerns with carbon containment, and large resupply requirements necessary to replace expended catalyst cartridges. An alternative approach to Bosch technology, labeled "Series-Bosch," employs a new system design with optimized multi-stage reactors and a membrane-based separation and recycle capability. Multi-physics modeling of the first stage reactor, along with chemical process modeling of the integrated system, has resulted in a design with potential to trade significantly better than previous Bosch technology. The modeling process and resulting system architecture selection are discussed.

Abney, Morgan B.↗

A new simulation model building process for use in dynamic systems integration research

A framework to build simulation models for aircraft dynamic systems integration is described. The objective of the framework is increased simulation model fidelity and reduced time required to develop and modify these models. The equations of motion for an elastic aircraft and their impact on the framework are discussed in broad terms. A software tool which automatically generates FORTRAN routines for tabular data lookups, the language used to develop a simulation model, and the structures for passing information into a simulation are discussed. A simulation variable nomenclature is presented. The framework has been applied to build an open-loop F/A-18 simulation model. This example model is used to illustrate model reduction issues. Current deficiencies in the framework are identified as areas for future research.

Arbuckle, P. Douglas↗

Biological production models as elements of coupled, atmosphere-ocean models for climate research

Process models of phytoplankton production are discussed with respect to their suitability for incorporation into global-scale numerical ocean circulation models. Exact solutions are given for integrals over the mixed layer and the day of analytic, wavelength-independent models of primary production. Within this class of model, the bias incurred by using a triangular approximation (rather than a sinusoidal one) to the variation of surface irradiance through the day is computed. Efficient computation algorithms are given for the nonspectral models. More exact calculations require a spectrally sensitive treatment. Such models exist but must be integrated numerically over depth and time. For these integrations, resolution in wavelength, depth, and time are considered and recommendations made for efficient computation. The extrapolation of the one-(spatial)-dimension treatment to large horizontal scale is discussed.

Platt, Trevor↗

Ch. 12. A Theoretical Approach to Management of Limited Attentional Resources to Support the m:N Operation in Advanced Air Mobility Ecosystem

Advanced air mobility (AAM) technologies incorporate increasingly autonomous systems that allow fully remote, independent, and intelligent operation of air vehicles to support the transportation of goods and passengers within and across urban and rural areas. With a myriad of automated technologies enabling the AAM ecosystem, the human operator’s role will likely be a passive supervisory monitor of the air vehicles, involving increasingly fewer humans (m) that manage many more autonomous systems (N), or m:N operations. Unfortunately, the human performance literature suggests that human operators will exhibit poor supervision of numerous autonomous agents due to the limits of attentional resources in the operators. In the general human information-processing model, a human operator exercises a limited pool of attentional resources to engage various information-processing stages including detecting, perceiving, comprehending, and predicting objects around them. Yamani and Horrey (2018) expanded the human information-processing model to characterize a tradeoff between information-processing demand and resource relief that automation brings in the context of automated driving. In their model, a driver interacting with an automated driving system is assumed to reallocate resources “freed” by automation to support other information-processing stages required for successful task performance. A future AAM ecosystem enabled by an orchestration of advanced automated systems, however, requires a single operator to interact with more than one air vehicle with varying levels and degrees of automated systems, making the traditional framework of human-automation interaction insufficient. To address this gap, we provide a review of the literature on situation assessment and trust, two constructs identified as critical for a fuller understanding of intimate and intricate interactions between a human operator and multiple air vehicles equipped with increasingly autonomous systems. Then, we propose an expansion of Yamani and Horrey’s (2018) model to motivate systematic research on the human operator’s role, identify factors that influence resource allocation and guide human-centered design of an interface supporting the m:N operation in the AAM environment.

Advanced Air Mobility↗

Intelligent alarming

This talk discusses the importance of providing a process operator with concise information about a process fault including a root cause diagnosis of the problem, a suggested best action for correcting the fault, and prioritization of the problem set. A decision tree approach is used to illustrate one type of approach for determining the root cause of a problem. Fault detection in several different types of scenarios is addressed, including pump malfunctions and pipeline leaks. The talk stresses the need for a good data rectification strategy and good process models along with a method for presenting the findings to the process operator in a focused and understandable way. A real time expert system is discussed as an effective tool to help provide operators with this type of information. The use of expert systems in the analysis of actual versus predicted results from neural networks and other types of process models is discussed.

Braden, W. B.↗

Integrating Theory and Practice: Applying the Quality Improvement Paradigm to Product Line Engineering

My assertion is that not only are product lines a relevant research topic, but that the tools used by empirical software engineering researchers can address observed practical problems. Our experience at NASA has been there are often externally proposed solutions available, but that we have had difficulties applying them in our particular context. We have also focused on return on investment issues when evaluating product lines, and while these are important, one can not attain objective data on success or failure until several applications from a product family have been deployed. The use of the Quality Improvement Paradigm (QIP) can address these issues: (1) Planning an adoption path from an organization's current state to a product line approach; (2) Constructing a development process to fit the organization's adoption path; (3) Evaluation of product line development processes as the project is being developed. The QIP consists of the following six steps: (1) Characterize the project and its environment; (2) Set quantifiable goals for successful project performance; (3) Choose the appropriate process models, supporting methods, and tools for the project; (4) Execute the process, analyze interim results, and provide real-time feedback for corrective action; (5) Analyze the results of completed projects and recommend improvements; and (6) Package the lessons learned as updated and refined process models. A figure shows the QIP in detail. The iterative nature of the QIP supports an incremental development approach to product lines, and the project learning and feedback provide the necessary early evaluations.

Stark, Michael↗

Description of statistical methods and a routine for determining the parameters of a model in processing experimental results

A computer routine is suggested for selecting the optimum parameters of a theoretical model and determining the errors in them due to errors in physical measurements and for evaluating the conformity of theory with the experiment. The paper describes the specification sequence for the input data and the format of the calculation results. Sample printouts are appended.

Usikov, D. A.↗

Integrated Bosch Process System Models for In-Situ Oxygen and Carbon Production

In-Situ Resource Utilization (ISRU) technology is a vital component to NASA’s mission of a sustainable presence on the Moon and Mars. Local resources can be leveraged to reduce resupply frequency and mass. Elements of the Bosch process, combined with the carbothermal reduction process, can produce oxygen on the lunar surface with minimal consumables. The Bosch process can also produce oxygen on the Martian surface by using the CO 2 -rich environment. Between both systems, adsorption pump, solar thermal energy, carbon formation reactor, and water recovery subsystems are modeled and integrated to create a functional model in MATLAB software. The model is used to simulate performance of the system and reduce mass, power, and volume requirements. This integrated system model provides a tool to scale ISRU technologies for oxygen and carbon production. The MATLAB model is created by developing a system of independent subsystem models that are solved for their quasi-steady state values which can be integrated with respect to time to determine the change in current states. A flexible time stepping method is used to ensure a high level of accuracy during periods of rapid change while still making use of a simple explicit integration method. The flexible time step is calculated for each independent subsystem and the minimum value from those is used as the overall time step. A flexible time step is calculated by dividing a resolution value, or the maximum change per time step, by the variables current rate of change. The maximum value from all points in space is used for subsystem models that contain multiple values. The process is done for every variable that is being monitored in each subsystem and the global minimum is used as that iteration’s timestep. Several assumptions used in the MATLAB model for fluid flow dynamics, such as 1-D gas flow through the sorption pump, are supported by modeling in Ansys Fluent software. The Lunar oxygen production system is outlined in Fig. 1. The carbothermal reduction subsystem uses solar energy to heat a mixture of lunar regolith and carbon powder to produce carbon monoxide. To begin, the carbon monoxide feeds to the modified Bosch subsystem along with hydrogen gas. The reactants then enter the carbon formation reactor where water and carbon powder are produced. Solar thermal energy is used to add energy to the reactor, but waste heat from the carbothermal process is another potential heat source. The water is collected and electrolyzed to produce hydrogen which reenters the Bosch subsystem, and the oxygen is stored for downstream use. The carbon powder is collected and feeds back into the carbothermal subsystem. The Martian oxygen production system uses the full Bosch process and is outlined in Fig 2. A CO 2 adsorption pump thermally cycles to scrub and pressurize CO 2 from the environment. Along with an initial supply of hydrogen, the reactants enter the Reverse Water Gas Shift Reactor (RWGSR) which produces carbon monoxide and water. Carbon monoxide and unreacted hydrogen enter the carbon formation reactor to produce water and carbon powder. The water is collected from both reactors and electrolyzed to reintroduce hydrogen and store oxygen for propellant production or life support. Carbon is removed from the carbon formation reactor and stored. The adsorption pump utilizes rapid cycle temperature swings within a stack of zeolite coated surfaces. The subsystem model solves 1-D quasi-steady conservation laws of the quasi-steady form, shown in Eq. 1, for the gas stream and heat exchange liquid to predict performance parameters such as breakthrough capacity and optimum cycle time. The source term S is used to capture interactions between the fluid flows and the sorbent. A quasi-steady-state scheme is used where no time derivatives appear in the governing equations, except for those in the source terms. This results in an autonomous system, where ∂F/∂x = ƒ(F). The fluxes F are provided at the inlet, and an explicit method is used to solve for the spatial distribution of F. The heat and mass flows to the sorbent are then extracted from the source terms. These flows are numerically integrated to produce a 1-D solution for the system’s state as a function of both time and space. The body of the adsorption pump is separated into two semi-independent models: the heat exchanger fluid flow and gas flow through the zeolite coated surfaces. Both models are solved using the above-described method to find a 1-D solution as a function of space and interact only once a timestep is taken. The interaction point is the sorbent through which all heat transfer between the two models must occur. Sorbent mass adsorption is calculated using the Lagergren model, shown in Eq. 2, where the transfer coefficient, λ D , is found by solving a system of nondimensionalized equations derived by using the heat and mass transfer analogy for transport phenomena. Using Grade 544 Type 13X zeolite as the sorbent material, the equilibrium concentration, θ eq , is calculated using the k-site Langmuir isotherm and fit parameters. Additionally, the enthalpy of adsorption used in the model is computed by interpolation of available data [1]. The subsystem model was validated using the Rapid Cycle Temperature Swing Adsorption (RC-TSA) pump. The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC). The solar thermal energy subsystem focuses on a solar concentrator concept with a heat exchanger to heat the reactants before entering the carbon formation reactor. The subsystem model assumes a fixed solar flux and reflector efficiency to calculate the reactant temperature given the incoming temperature, pressure, and exchanger geometry. The receiver is a custom manufactured series of copper blocks with serpentine channels to increase its surface area and the residence time of the reactants to heat up to 550 °C. The subsystem model was validated using a heat exchanger developed at NASA Glenn Research Center (GRC).

In situ Resource Utilization↗

Aircraft adaptive learning control

The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

Lee, P. S. T.↗

Spatial quantification of maps or images - Cell size or pixel size implications

The paper discusses spatial quantification of maps or images. Spatial accuracies evaluated by mapping and inventory measures were observed with a range of cell sizes for a 10.36 sq km soil survey segment. The distribution of interboundary distances in a map was evaluated as unique, characterizing information; experimentally observed relationships between accuracy and cell size and interboundary distance distribution parameters and cell size led to a model of the process of spatial quantization. Grid positioning effects were evaluated and were significant only at the level of individual mapping units; two generations of 'universal' process models were derived, implemented, and evaluated.

Wehde, M. E.↗

Combustion Fundamentals Research

Increased emphasis is placed on fundamental and generic research at Lewis Research Center with less systems development efforts. This is especially true in combustion research, where the study of combustion fundamentals has grown significantly in order to better address the perceived long term technical needs of the aerospace industry. The main thrusts for this combustion fundamentals program area are as follows: analytical models of combustion processes, model verification experiments, fundamental combustion experiments, and advanced numeric techniques.

Source record↗

Transient analysis of chilldown in a cryogenic transfer line

A numerical model was developed, with the SINDA'85/FLUINT program, for calculating the thermal and hydrodynamic transients that occur during the chilldown of a cryogenic transfer line, using a well documented test case to validate the modeling process. Using this model, a total of ten cases were analyzed to evaluate the effects of variable inlet valve position, inlet pressures, and the use of an internal flow liner to promote nucleate boiling. It was found that an efficient transfer line cooldown can be achieved if the inlet flow is throttled, to reduce the flow rate and quality, and an internal flow liner such as Teflon is used.

Martin, T.↗

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗

Porosity Prediction and Detection During Composite Cure Using Simulation and Ultrasonic In-Situ Inspection Inside and Autoclave

Composite materials offer unique benefits in aerospace applications such as increased strength-to-weight ratio and improved fatigue properties. They are increasingly being used in major commercial aircraft programs. However, current processing methods can lead to defects in composite parts, which are currently identified using post-manufacturing inspection methods. A cure defects process model has been developed to predict the formation of manufacturing defects (e.g., porosity and fiber waviness) in composites based on the cure parameters and part geometry. However, a capability to directly validate porosity during cure did not exist. Validation methods included comparing resin pressure measured during cure with predictions by the process model and inspection/microscopy after cure. This study developed a high-temperature ultrasonic inspection system to detect porosity defects in composites during autoclave cure and experimentally verify the predictions of the model. The system operated inside an autoclave within an enclosure cooled by intermittent liquid nitrogen(LN2) injections. A high-temperature 2.25 MHz ultrasonic transducer was utilized to transmit ultrasonic waves through the tool plate and into the composite material and to measure the amplitude and time of flight of the reflected waves with a 1 mm × 1 mm resolution. Porosity was observed via the ultrasonic reflections, which experienced increased attenuation in regions of high porosity. Distinct regions of increased porosity were present due to uneven pressure across the panel, which was driven by an intentional misfit between the flat caul plate and the tapered composite panel with ply drops. These observations matched the predictions of the model using the inputs from the experiment (e.g., part material and geometry, cure cycle) and were validated by post-cure ultrasonic inspection and micrographs. The in-situ inspection system was able to successfully provide defect detection and localization and can be applied to future manufacturing of composite structure for aerospace applications.

Porosity↗

Modelling System Processes to Support Uncertainty Analysis and Robustness Evaluation

In the use of advanced systems control techniques in the development of a dynamic system, results from effective mathematical modelling is required. Historically, in some cases the use of a model which only reflects the "expected" or "nominal" important -information about the system's internal processes has resulted in acceptable system performance, but it should be recognized that for those cases success was due to a combination of the remarkable inherent potential of feedback control for robustness and fortuitously wide margins between system performance requirements and system performance capability. In the cases of a CELSS development, no such fortuitous combinations should be expected, and it should be expected that the uncertainty in the information on the system's processes will have to be taken into account in order to generate a performance robust design. In this paper, we develop one perspective of the issue of providing robustness as mathematical modelling impacts it, and present some examples of model formats which serve the needed purpose.

Blackwell, Charles↗

Mapping Past, Present, and Future Climatic Suitability for Invasive Aedes Aegypti and Aedes Albopictus in the United States: A Process-Based Modeling Approach Using CMIP5 Downscaled Climate Scenarios

The ongoing spread of the mosquitoes, Aedes aegypti and Aedes albopictus, in the continental United States leaves new areas at risk for local transmission of dengue, chikungunya, and Zika viruses. All three viruses have caused major disease outbreaks in the Americas with infected travelers returning regularly to the U.S. The expanding range of these mosquitoes raises questions about whether recent spread has been enabled by climate change or other anthropogenic influences. In this analysis, we used downscaled climate scenarios from the NASA Earth Exchange Global Daily Downscaled Projections (NEX GDDP) dataset to model Ae. aegypti and Ae. albopictus population growth rates across the United States. We used a stage-structured matrix population model to understand past and present climatic suitability for these vectors, and to project future suitability under CMIP5 climate change scenarios. Our results indicate that much of the southern U.S. is suitable for both Ae. aegypti and Ae. albopictus year-round. In addition, a large proportion of the U.S. is seasonally suitable for mosquito population growth, creating the potential for periodic incursions into new areas. Changes in climatic suitability in recent decades for Ae. aegypti and Ae. albopictus have occurred already in many regions of the U.S., and model projections of future climate suggest that climate change will continue to reshape the range of Ae. aegypti and Ae. albopictus in the U.S., and potentially the risk of the viruses they transmit.

process-based modeling↗

Modeling Temporal Processes in Early Spacecraft Design: Application of Discrete-Event Simulations for Darpa's F6 Program

While the ability to model the state of a space system over time is essential during spacecraft operations, the use of time-based simulations remains rare in preliminary design. The absence of the time dimension in most traditional early design tools can however become a hurdle when designing complex systems whose development and operations can be disrupted by various events, such as delays or failures. As the value delivered by a space system is highly affected by such events, exploring the trade space for designs that yield the maximum value calls for the explicit modeling of time.This paper discusses the use of discrete-event models to simulate spacecraft development schedule as well as operational scenarios and on-orbit resources in the presence of uncertainty. It illustrates how such simulations can be utilized to support trade studies, through the example of a tool developed for DARPA's F6 program to assist the design of "fractionated spacecraft".

trade space exploration↗