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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dielectric screening at TMD:hBN interfaces: Monolayer-to-bulk transition, local-field effect, and spatial dependence

The dielectric effects of a substrate have been shown to be important for modulating the electronic properties of an adsorbate, especially in van der Waals heterostructures. Here, using the first-principles dielectric embedding GW approach within the framework of many-body perturbation theory, we perform a case study on the dielectric screening effects of hexagonal boron nitride (hBN) on various transition-metal dichalcogenides (TMDs). We consider three systems, monolayer MoS 2 , bilayer MoS 2 , and a mixed WS 2 /MoS 2 bilayer adsorbed on hBN, and examine three aspects of the substrate dielectric screening: (i) the thickness dependence and the monolayer-to-bulk transition, for which we consider the effects of one-, two-, three-, and four-layer hBN; (ii) the local-field effect, for which we numerically assess a common approximation of neglecting the in-plane local-field components of the substrate polarizability; and (iii) the spatial dependence, for which we consider the mixed WS 2 /MoS 2 bilayer adsorbed on hBN with either side facing the substrate. Finally, our results provide quantitative insight into how the substrate screening effects can be leveraged for band structure engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Protein–Protein Complex Stability Controls Substrate Scope in a β‐Ketoacyl‐ACP Reductase Specific for Medium Chains

Assembly-line enzymes carry out multistep synthesis of important metabolites by using acyl carrier proteins (ACPs) to shuttle intermediates along defined sequences of active sites. Despite longstanding interest in reprogramming these systems for metabolic engineering and biosynthetic chemistry, the mechanisms underlying their reaction order remain poorly understood and difficult to control. In this work, we describe a β-ketoacyl-ACP reductase from Pseudomonas putida (PpFabG4) with an unusual selectivity for medium chains and use it to explore the molecular basis of substrate specificity in enzymes that pull intermediates from fatty acid synthesis, a common route to specialized products. X-ray crystallography shows no obvious barriers to short-chain binding. Molecular simulations and supporting mutational analyses indicate that substrate preference arises instead from a weak enzyme–ACP interaction that is stabilized by medium acyl chains but not by short chains. Indeed, mutations that strengthen this interaction for PpFabG4 or weaken it for EcFabG, an Escherichia coli β-ketoacyl-ACP reductase with a broad substrate specificity, can enhance or reduce activity on short-chain substrates by over 100-fold. Our findings show how the stability of enzyme-ACP interactions can control substrate scope in promiscuous enzymes and guide the exchange of intermediates between (and within) assembly-line systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Alternative Designs and Analyses for Destructive and Non-replicable Gauge R &R Studies

This article presents new designs and their analyses for destructive and non-replicable gauge R & R studies. Less restrictive assumptions about destructive measurements on “similar” parts and non-replicable measurements made over time or space than have been made previously in the literature are proposed; only couples of “nearly identical” parts are proposed for destructive measurements and quadruples involving two operators are proposed for non-replicable measurements that avoid having to estimate a common trend and removing it. In this work, these new designs based on balanced incomplete block designs and their analyses are illustrated with simulated examples that confirm that with them such measurements systems can be assessed.

42 ENGINEERING↗
DOE OSTI2023

Diverging climate response of corn yield and carbon use efficiency across the U.S.

Abstract In this paper, we developed an open-source package to analyze the overall trend and responses of both carbon use efficiency (CUE) and corn yield to climate factors for the contiguous United States. Our algorithm enables automatic retrieval of remote sensing data through the Google Earth Engine (GEE) and U.S. Department of Agriculture (USDA) agricultural production data at the county level through application programming interface (API). Firstly, we integrated satellite products of net primary productivity and gross primary productivity based on the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and climatic variables from the European Centre for Medium-Range Weather Forecasts. Secondly, we calculated CUE and commonly used climate metrics. Thirdly, we investigated the spatial heterogeneity of these variables. We applied a random forest algorithm to identify the key climate drivers of CUE and crop yield, and estimated the responses of CUE and yield to climate variability using the spatial moving window regression across the U.S. Our results show that growing degree days (GDD) has the highest predictive power for both CUE and yield, while extreme degree days (EDD) is the least important explanatory variable. Moreover, we observed that in most areas of the U.S., yield increases or stays the same with higher GDD and precipitation. However, CUE decreases with higher GDD in the north and shows more mixed and fragmented interactions in the south. Notably, there are some exceptions where yield is negatively correlated with precipitation in the Missouri and Mississippi River Valleys. As global warming continues, we anticipate a decrease in CUE throughout the vast northern part of the country, despite the possibility of yield remaining stable or increasing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Survey on the Design, Detection, and Prevention of Pre-Silicon Hardware Trojans

The complexity of the semiconductor design lifecycle and globalized manufacturing process creates concern over the threat of deliberate malicious alterations, or hardware Trojans, being inserted into microelectronic designs. This has resulted in a significant corpus of hardware Trojan research including Trojan design and benchmarking efforts and development of corresponding metrics and detection and prevention techniques, over the last two decades. In this survey, we first highlight efforts in Trojan design and benchmarking, followed by a cataloging of seminal and recent works in Trojan detection and prevention and their accompanied metrics. Given the volume of literature in this field, this survey considers only pre-silicon techniques. We make this distinction between pre- and post-silicon to properly scope and provide appropriate context into the capabilities of existing hardware Trojan literature. Each major section (design, prevention, and detection) is accompanied by insights, and common pitfalls, which we highlight can be addressed by future research.

42 ENGINEERING↗
DOE OSTI2023

Independence of Environmental and Mechanical Damages on Silicone Adhesive Stored in a Thermo-Oxidative Environment

Abstract Elastomeric polymer materials hold a special place in today’s industrial sectors with respect to structural application needs. Low quality materials are detrimental to industries like aerospace, and automotive engineering. Assessment of the durability of elastomers for structural applications has been of much interest among the literary circles for decades and new materials keep outperforming the existing ones. Polymeric adhesives are one of the most abundantly used materials in these industries. All polymeric materials get damaged when in contact with aggressive environments in presence of high temperature and oxygen. Commonly referred to as thermo-oxidation, this environment exposes the material to heat and oxidation reactions in presence of oxygen. Resultantly, during service life, the damage to the polymer matrix is primarily caused by two factors: mechanical damage and environmental aging. Environmental aging is an irreversible phenomenon caused by changes in the molecular structure while mechanical damage maintains the shape of the polymer matrix, and the deterioration is mostly due to polymer chain mobility. Environmental aging can be caused by a single environmental agent or by a synergized impact of several environmental elements. Increasing temperature is found to be proportional to decreasing tensile strength and toughness of material. The rate and extent of degradation can be accessed by scrutinizing the changes in constitutive behavior of material through mechanical and chemical properties. Accelerated thermal aging is among the most common modes of process related degradation, leading generally to chain scission, and crosslinking phenomena and reduced resistance to fracture stress, and strain. In this experimental study, our goal is to separate the environmental degradation from mechanical damage. A silicone-based adhesive was aged in thermo-oxidative at (0%RH) aging environment. The damage and decay mechanisms have been used to draw a distinction between environmental degradation and mechanical damage. Material characterization included uniaxial tensile test (failure and cyclic) and scanning electron microscopy (SEM) tests on as-received and aged samples. Aging was conducted at three different temperatures (60°C, 80°C and 95°C) and six different exposure durations (1, 3, 10, 30, 90 and 200 days). This work confirms that environmental damage is superposed on top of the mechanical damage, and thus, they are separable. The total mechanical and environmental damage is a synergized effect of all exposure conditions and parameters involved i.e., aging time, temperature, and oxygen. The chemistry and mechanics of the polymer degradation were found to be in good agreement with each other.

Alazhary, Sharif↗
DOE OSTI2020

Chromatographic Modeling of 1-Foot Detritiation Test Column Results for the Optimization of Regeneration Time

This report documents the methods and results of a modeling study on a series of data generated by 1-foot test columns for the Water Detritiation project. In order to compliment modeling work already in progress on this project, a purely empirical curve-fitting approach is used in this study to determine chromatographic performance indicators such as retention time, curve width, and the number of chromatographic stages. The data used in this study comes from four sets of chromatographic test separations performed in March through May of 2017 using 1-foot columns. All are using the same flow rates and temperature (room temperature, nominally 25 C°). The first set of data (referred to in this report as the Column 1 data) is a series of twelve breakthrough curve measurements. Prior to each of these twelve runs, the column was regenerated by flowing hydrogen gas through the column, for increasing amounts of time, ranging from 2 hours to 25 hours. The second set of data (referred to as the Column 2 data) is comprised of five measurements of breakthrough curves measured in similar fashion as the Column 1 data, across a range of regeneration times from 2 to 21 hours. The third set of data (referred to as the Purge data) is of three breakthrough curves, measured after a regeneration time of 8 hours, which takes place after a nitrogen purge of 15, 30, or 45 minutes. The fourth data set is a series of five breakthrough curve measurements using a 2 nd batch of stationary phase, taken after regeneration times ranging from 2 to 20 hours. The overall modeling approach is as follows. First, the data is pre-processed for formatting, artifact removal, and is normalized. The data is then fit by integrated versions of four common chromatographic models. The best model is chosen based on the predictive performance of the model, and chromatographic performance values are calculated based on the best model’s fit parameters. Each of these processes are detailed below.

42 ENGINEERING↗
DOE OSTI2022

Aerosol Inlets for a Mid-Sized Uncrewed Aerial System (UAS)

The purpose of this technical report is to document the efforts to design and test two inlet systems for aerosol sampling suitable for deployment on a medium-sized fixed-wing Uncrewed Aerial System (UAS). This work, which was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility, was conducted at the Pacific Northwest National Laboratory (PNNL) for the ARM Aircraft Facility (AAF) starting in November 2017. The current work is a part of AAF efforts to instrument the ArcticShark (a mid-sized UAS owned and operated by the AAF) for atmospheric research and develop a scientific payload for deployment on a similar-sized UAS with minimal adaptation and integration. An aerosol inlet system is necessary to sample and transport ambient air sample to the scientific instrumentation with minimal distortions to the aerosols. Two isokinetic aerosol inlets were designed: the first is a simple passive system for a single instrument suitable to be installed in a wing pylon; the second is a system with active control designed to sample and distribute air among several heterogeneous instruments and to provide basic humidity control of the air sample so that the measured aerosol parameters should correspond to “dry” conditions (a common requirement). Both systems could be easily adapted for deployment on another platform and/or with a different set of instrumentation. Several conducted flight tests showed that the inlets’ performance met our design goals.

42 ENGINEERING↗
DOE OSTI2022

Engineering Citrobacter freundii using CRISPR/Cas9 system

The CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR associated proteins) system is a useful tool to edit genomes quickly and efficiently. However, the use of CRISPR/Cas9 to edit bacterial genomes has been limited to select microbial chassis primarily used for bioproduction of high value products. Thus, expansion of CRISPR/Cas9 tools to other microbial organisms is needed. Here, our aim was to assess the suitability of CRISPR/Cas9 for genome editing of the Citrobacter freundii type strain ATCC 8090. We evaluated the commonly used two plasmid pCas/pTargetF system to enable gene deletions and insertions in C. freundii and determined editing efficiency. The CRISPR/Cas9 based method enabled high editing efficiency (~91%) for deletion of galactokinase (galk) and enabled deletion with various single guide RNA (sgRNA) sequences. To assess the ability of CRISPR/Cas9 tools to insert genes, we used the fluorescent reporter mNeonGreen, an endopeptidase (yebA), and a transcriptional regulator (xylS) and found successful insertion with high efficiency (81-100%) of each gene individually. These results strengthen and expand the use of CRISPR/Cas9 genome editing to C. freundii as an additional microbial chassis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Carbon Capture from ArcelorMittal Hot Briquetted Iron Plant Using Air Liquide Cryocap™ FG Technology – FEED Study

The process of steel production is energy and carbon intensive with global average energy consumption of 5.5 MWh/tonne of steel and CO2 emission intensity of 1.83 tonne CO2/tonne of steel. The steel making process has inherent CO2 emissions from mineral conversion and is considered major contributors to the global carbon emissions. The steel industry is responsible for 8% of global carbon emissions. The main objective of this research project is to execute and complete a front-end engineering and design (FEED) study for a commercial-scale, carbon capture project that separates 95% of the total CO2 emissions at the ArcelorMittal’s Hot Briquetted Iron (HBI) plant in Portland, TX (Figure 1). The HBI is an ore-based metallic that is used as high-grade feedstock for high-quality steel via an Electric Arc Furnace (EAF) route. The HBI plant produces 2.0 million metric tonnes of high-quality HBI and emits approximately 1 million tonnes CO2/yr. The capture system is a Pressure Swing Adsorption (PSA) system assisted Cryocap™ FG technology (Figure 2). The captured CO2 will be pipeline grade and will be geologically stored in a facility within 10 miles of the CO2 source. The Host Site location in Corpus Christi, TX, is near hydrocarbon processing facilities and near Environmental Justice (EJ) and Qualified Opportunity Zone (QOZ) communities. Due to the location of the Host Site, the retrofit project offers the ability to demonstrate how a workforce focused on the fossil energy sector can be redirected to the clean- energy sector. The Air Liquide Cryocap™ capture technology is a proven technology and has been extensively examined for large industrial applications. It has been shown to be applicable to a variety of industrial applications including the steel industry. Cryocap™ FG (specific setup for Flue Gas application) consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The scope of this study incorporates completing FEED study of the CO2 capture system which includes point-source CO2 capture and balance-of-plant; Business Case Analysis (BCA) outlining the current and projected volumes of the steel plant’s point sources of CO2 and the potential utilization of tax credits, including its projected revenue and duration; Life Cycle Analysis (LCA); Environmental Justice Analysis; Economic Revitalization and Job Creation Outcomes Analysis; and Workforce Readiness Plan. The plant design work was divided into two components: Inside Battery Limits (ISBL) and Outside Battery Limits (OSBL). The ISBL focuses on the capture system, while the OSBL focuses on the utility feeds and ducting from the plant to the capture system. Various design and engineering deliverables will be developed to define commodity quantities, equipment specifications, and labour effort required to execute the project. These FEED study deliverables will be prepared with the intent to develop an overall project capital cost estimate consistent with an AACE Class 3 estimate. The modular approach for the Cryocap™ FG that is being designed for this study integrates compression, PSA, and cryogenic “bricks” to achieve the desired CO2 capture rates. This carbon capture system integrates easily with the existing plant, thus reducing project costs and risks. It is also capable of managing impurities such as nitrogen oxides (NOx), sulfur oxides (SOx), mercury, hydrocarbons, and particulate matter. The capture system has a smaller footprint than amine-based systems. The two-step process uses PSA to preconcentrate the CO2 in the feedstream and then uses the cryogenic portion to purify and compress the resulting high purity CO2 product. This combination of purification and compression (i.e., process intensification) significantly reduces the CAPEX associated with use of a separate compressor commonly utilized for amine solvent-based systems. Successful completion of the FEED study will provide DOE with a detailed understanding of the costs for scaling up this proven capture technology for commercial applications at industrial facilities.

42 ENGINEERING↗
DOE OSTI2022

A novel approach to build algal consortia for sustainable biomass production

In the last decade, microalgae have reemerged as a feedstock for biofuels and a diverse suite of bioproducts. Yet, considerable challenges must be overcome before algal biofuels and bioproducts become technoeconomically viable. At present, single algal strain selected for particular phenotypic traits, such as maximum specific growth rate or lipid content, are commonly scaled for cultivation in open, outdoor raceway ponds due to the low capital costs of these systems. Although this monoculture approach may maximize the production of end products, monocultures are particularly susceptible to crashes associated with environmental and biological variability. An approach that has been proposed to generate more productive and stable microalgal crops is the use of eco-engineered communities, or consortia. Yet, attempts to construct productive consortia have not been consistently successful. We argue that failures stem from the lack of an eco-engineering approach to design species combinations. Here, we used an in silico method to build consortia before testing their performance against monocultures. Focusing on consortia of Nannochloropsis and Microchloropsis, we measured growth of strains along gradients of light, temperature, and salinity and used a functional dispersion approach to generate over 8000 functionally-diverse consortia combinations. We tested the 50 most functionally diverse consortia in a laboratory experiment and found that consortia overwhelmingly outperformed monocultures. Indeed, overyielding (OY) and a positive net biodiversity effect (NBE) was found respetively in 8%-86% and 88-92% of consortia combinations over the different experimental phases. To our knowledge, this is the first application of an in silico approach to design functionally diverse consortia before laboratory and field testing. Furthermore, our results highlight the importance of employing a functional diversity approach for consortia design.

09 BIOMASS FUELS↗
DOE OSTI2024

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗
DOE OSTI2026

Insights from Initial Engineering Designs of Point Source Capture at Industrial Facilities

Initial engineering design studies examining the application of state-of-the-art carbon capture technology at industrial plants contain generally overlooked real-world design considerations for near-term deployment of point source capture (PSC). The implementation of PSC across a wide range of industrial applications presents unique challenges associated with fluctuating CO<sub>2</sub> concentrations, flue gas composition, and utility and land availability. In this article, seven recent industrial retrofit PSC projects are reviewed to investigate the impact of site-specific factors on project design and cost. Across the seven projects, three capture technology classes and four industrial applications are considered, allowing insight into industry-specific opportunities for PSC technology synergy. Common challenges across projects and proposed design solutions are highlighted to propagate ideas and solutions to close the technology gaps and accelerate learning rates.

FEED Studies↗
DOE OSTI2023

Laser Speckle Pattern Stability in Hypersonic Regimes for Experimental Mechanics and Metrological Studies

Here, an empirical study assessing the suitability of laser speckle patterns for use in experimental mechanics research conducted at hypersonic conditions is presented. Speckle patterns generated via coherent optical scattering from a gold-coated graphite surface inserted into a Mach 10 air stream were collected and analyzed using Computer-Aided Speckle Interferometry using two methodologies: a typical spanwise approach involving increasing temporal span between image pairs, and a sequential approach that utilizes a combination of temporal re-referencing and spatial resampling. Results were characterized for spatial-temporal stability and variance. Our observations demonstrate that optical methods relying on stable and properly formed speckle patterns can be used in a hypersonic regime at various Reynolds numbers and common camera frame rates, but the technique is sensitive to the conditions of the airflow and the processing methodology chosen.

42 ENGINEERING↗
DOE OSTI2022

High Order Wall-Modeled Large-Eddy Simulation on Mixed Unstructured Meshes

In the present study, an algebraic equilibrium wall model previously developed for hexahedral elements is extended to handle mixed meshes including prismatic, tetrahedral, and pyramidal elements in the context of a discontinuous high-order method. This extension is needed for complex geometries, for which high-order mixed elements (e.g., tetrahedral and pyramidal elements) are often necessary near solid walls to avoid meshing challenges. Various design decisions are discussed to achieve the best performance on massively parallel CPU/GPU architectures for a production-level high-order large-eddy simulation solver based on the flux reconstruction/correction procedure via reconstruction method, hpMusic. The extension to other elements is first evaluated using a benchmark channel flow problem at various Reynolds numbers. After that, flow over the NASA high-lift Common Research Model (CRM-HL) from the 4th AIAA High-lift Prediction Workshop is computed to further test the new implementation. Computational results at the third- and fourth-order accuracies are compared with experimental data.

Engineering↗
DOE OSTI2024

An MPMD approach coupling electromagnetic continuum mechanics approximations in ALEGRA

In this work, two complementary approximations for describing aspects of continuum electromagnetics in moving media are discussed: electroquasistatic and magnetoquasistatic. Each has been implemented in the finite element shock code ALEGRA for modeling dynamic electromechanical phenomena on typical engineering time scales, with fully integrated circuit coupling. The approximations can be obtained by consistent asymptotic balancing of Maxwell’s equations relative to timescales associated with magnetic diffusion, charge relaxation, and electromagnetic wave propagation. In ALEGRA, the electroquasistatic approximation is used for ferroelectric (FE) modeling, while the magnetoquasistatic approximation is used for magnetohydrodynamic (MHD) modeling. In this paper we introduce for the first time a detailed derivation of a useful quasi-steady “low-R m ” variant of the MHD approximation applicable for cases, such as with detonators, where the thermodynamic pressure arising from Joule heating dominates over magnetic forces. An additional purpose of this paper is to present a coupling mode using Multiple Program-Multiple Data (MPMD) message passing communication that allows the user to run 3D FE problems together with 2D and/or 3D MHD problems with the respective simulation domains coupled through a common circuit equation. The MPMD coupling capability is used here to model the dynamic coupling of a notional ferroelectric generator with an RP-87 exploding bridgewire detonator. The simulated bridgewire heats up and bursts under current generated by simulated depoling of the ferroelectric generator, as a demonstration of the MPMD capability.

42 ENGINEERING↗
DOE OSTI2026

Biochemical parallels between catabolic pathways for lignin-associated aromatic dimers

Lignin is one of the most common biopolymers on Earth. In nature, lignin is primarily deconstructed by fungi into mixtures of aromatic compounds that are then assimilated by bacteria and fungi. Industrially, lignin is primarily generated as a byproduct of pulp and paper production and burned for process heat. However, if the appropriate assimilatory pathways were identified, deconstructed lignin could be funneled into value-added products using engineered bacteria. Foundational work has described pathways for assimilation of diverse monomeric aromatic compounds such as protocatechuate, ferulate, and syringate, as well as select dimers including those with β-O-4 and 5-5 interunit linkages. Recent advances have elucidated additional pathways for dimer assimilation, including pathways for new substrates as well as parallel pathways for previously characterized substrates. Comparing these dimer assimilation pathways can illuminate the underlying biochemical logic of assimilation for lignin-associated aromatic dimers and provide opportunities for metabolic engineering to enhance lignin valorization.

Sphingomonas↗
DOE OSTI2024

Hydrodynamic Test Requirements Process Improvements

Hydrodynamic testing at Los Alamos National Laboratory would benefit from a process improvement for the requirements process. Cameo was used as a digital solution for requirements management to allow Lead Engineers to track requirements more effectively. This was identified as a process improvement throughout this Capstone project. This report includes a project proposal, business case, literature review, methodology, project plan, data analysis, decision-making report, financial analysis report, discussion, and conclusion. Initially, this project focused on figuring out a solution for the hydrotest requirement process improvements. The scope narrowed to focus on the use of Cameo for requirement capture and management. During this Capstone, four tests had digital models produced for requirements management in Cameo. The initial model was the baseline, with core requirements used across the tests. Commonalities in tests were used and the core requirements allowed for process efficiencies. In the data analysis, it was seen that overall, the implementation of using Cameo for requirements resulted in a decreasing trend for both schedule and normalized cost. Tests have different complexity levels which is also a factor in how long the requirements process will take. Additional data is needed to continue analyzing process improvements. Through decisionmaking and financial analysis, the recommendation was to use Cameo for requirements process improvement. Multiple experts provided feedback for requirements that were then captured within models. Numerous tangible and intangible benefits were identified with this process improvement. For return on investment, the metric of success was schedule reduction, which was overall seen. Four tests were analyzed, so future analysis will be needed. There is also not a great financial risk because the main cost would be purchasing more licenses. Individuals must generate requirements whether using this software or not. Overall, training is needed to help improve the skillsets of Lead Engineers but is already being supported on a regular frequency. A desktop guide was started associated with explaining the process, however, it is a work in progress. The team plans on adding additional information in the digital models to help status when requirements are met using verification methods and artifacts. From working on this project an improved understanding of Cameo and requirements was the result. There are future opportunities to extend the usage for requirements management and progress will continue after this project.

99 GENERAL AND MISCELLANEOUS↗