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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High speed butt joining of 1” thick 2139-T8

Thick plate (=1”) butt joining of Al alloys is challenging due to high tool forces, uneven material flow, and heat distribution in the through-thickness direction. Tool design and welding parameters used for executing thick plate butt joining have remained mostly static over the past decade. Reported welding speeds that produce viable joint strength (mostly on 6xxx alloys) typically range below 100 mm/min (4inches /min). Researchers at Pacific Northwest National Laboratory (PNNL) in association with Ground Vehicle Systems Center (US Army GVSC) have been working to demonstrate greater joining efficiency at higher welding speeds in a 1” thick AA2139-T8 plate. Using innovative tool features and effective force and temperature control a joint efficiency of 80% was demonstrated at a welding speed of 7 inches /min (178mm/min).

Das, Hrishikesh↗
DOE OSTI2013

Mercury contaminated sediment sites—An evaluation of remedial options

Mercury (Hg) is a naturally-occurring element that is ubiquitous in the aquatic environment. Though efforts have been made in recent years to decrease Hg emissions, historically-emitted Hg can be retained in the sediments of aquatic bodies where they may be slowly converted to methylmercury (MeHg). Consequently, Hg in historically-contaminated sediments can result in high levels of significant exposure for aquatic species, wildlife and human populations consuming fish. Even if source control of contaminated wastewater is achievable, it may take a very long time, perhaps decades, for Hg-contaminated aquatic systems to reach relatively safe Hg levels in both water and surface sediment naturally. It may take even longer if Hg is present at higher concentration levels in deep sediment. Hg contaminated sediment results from previous releases or ongoing contributions from sources that are difficult to identify. Due to human activities or physical, chemical, or biological processes (e.g. hydrodynamic flows, bioturbation, molecular diffusion, and chemical transformation), the buried Hg can be remobilized into the overlying water. Hg speciation in the water column and sediments critically affect the reactivity (i.e. conversion of inorganic Hg(II) to MeHg), transport, and its exposure to living organisms. Also, geochemical conditions affect the activity of methylating bacteria and its availability for methylation. This review paper discusses remedial considerations (e.g. key chemical factors in fate and transport of Hg, source characterization and control, environmental management procedures, remediation options, modeling tools) and includes practical case studies for cleaning up Hg-contaminated sediment sites. -- Highlights: ► Managing mercury-contaminated sediment sites are challenging to remediate. ► Remediation technologies are making a difference in managing these sites. ► Partitioning plays a dominant role in the distribution of mercury species. ► Mathematical models can be used to help us understand the chemistry and processes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗
DOE OSTI2026

Constellation: The autonomous control and data acquisition system for dynamic experimental setups

The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These environments frequently undergo modifications, such as the inclusion of different auxiliary devices depending on the experiment or facility, adding further complexity. The successful management of such dynamic configurations demands a flexible and robust system capable of controlling data acquisition, monitoring experimental setups, enabling seamless reconfiguration, and integrating new devices with limited effort. This paper presents Constellation, a flexible and network-distributed control and data acquisition software framework tailored to laboratory and beamline environments, that addresses the limitations of existing solutions. The framework is designed with a focus on extensibility, providing a streamlined interface for instrument integration. It supports efficient system setup via network discovery mechanisms, promotes stability through autonomous operational features, and provides comprehensive documentation and supporting tools for operators and application developers such as controllers and logging interfaces. At the core of the architectural design is the autonomy of the individual components, called satellites, which can make independent decisions about their operation and communicate these decisions to other components. This paper introduces the design principles and framework architecture of Constellation, presents the available graphical user interfaces, shares insights from initial successful deployments, and provides an outlook on future developments and applications.

Autonomy↗
DOE OSTI2025

Spectroscopic Online Monitoring: Using a Multi-Track Visible Spectrometer to Facilitate a Mass Balance Study in a Simulated TALSPEAK Process

Nuclear energy is a promising low-carbon energy candidate to meet the increased demand for green energy, where the integration of fuel recycling can have significant benefits for material usage and waste reduction. Utilizing in situ monitoring tools can provide ample opportunities to better control and safeguard nuclear material recycle processes while also offering knowledge and insight into real-time solution properties. The simultaneous measurement of analytical targets in multiple process locations can enable real-time mass balance and material accountancy calculations. This is demonstrated here with a mass balance study of Nd 3+ on countercurrent aqueous/organic metal extraction within a single centrifugal contactor. The Nd 3+ concentration was simultaneously monitored at the inlets and outlets of both aqueous and organic phases using a visible absorbance detector that allowed for the simultaneous measurement of up to six locations. The Nd 3+ concentration was calculated by using chemical data science algorithms, where model training sets were collected on a single track of the detector. The discussion includes addressing the challenges of using a model collected on a single track and applying it as a model across the other tracks on the detector. Each track of the detector corresponds to one measurement location on the contactor. The difference in the integrated moles of Nd 3+ between the inlet and outlet at the end of the experiment was near zero, indicating that the mass balance of this experiment was maintained. Overall, the online spectroscopic monitoring was able to follow changing solution conditions and accurately measure the concentration of Nd 3+ in different locations within the contactor system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios

Abstract Recent water infrastructure planning models demonstrate that explicitly accounting for hydrological changes in long‐term water planning reduces costs and increases system robustness. However, current models do not consider the effects of other changes occurring in the system over long time horizons, namely technology and policy innovation. By leveraging state‐of‐the‐art dynamic control techniques, we propose a suite of tools that explicitly relate hydrologic change, technology innovation, and policy interventions to system‐level water costs. We design robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states, for example, treatment cost and diversification improvements, deployment times, and demand reduction campaigns. Our approach circumvents the need to pre‐assign probabilities to innovation scenarios and, instead, directly calculates the effects of technology, policy, and hydrology variations on system cost and planning strategies to identify avenues of impactful innovation. These tools can support technology development hubs, urban, state, and federal water planners in anticipating cost implications of technology and policy innovation at the local level, and prioritizing high‐impact innovation goals based on quantitative targets. Results for the case study of Santa Barbara, California identify high‐value innovation attributes for the city as well as combinations of innovation attributes across technologies and policies, and quantify their potential utility cost reductions.

13 HYDRO ENERGY↗
DOE OSTI2020

A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming

Abstract Unraveling the drivers controlling community assembly is a central issue in ecology. Although it is generally accepted that selection, dispersal, diversification and drift are major community assembly processes, defining their relative importance is very challenging. Here, we present a framework to quantitatively infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP). iCAMP shows high accuracy (0.93–0.99), precision (0.80–0.94), sensitivity (0.82–0.94), and specificity (0.95–0.98) on simulated communities, which are 10–160% higher than those from the entire community-based approach. Application of iCAMP to grassland microbial communities in response to experimental warming reveals dominant roles of homogeneous selection (38%) and ‘drift’ (59%). Interestingly, warming decreases ‘drift’ over time, and enhances homogeneous selection which is primarily imposed on Bacillales. In addition, homogeneous selection has higher correlations with drought and plant productivity under warming than control. iCAMP provides an effective and robust tool to quantify microbial assembly processes, and should also be useful for plant and animal ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Wavelet analysis of MR functional data from the cerebellum

The main goal of this project was to create a computer algorithm based on wavelet analysis of BOLD signals, which automatically diagnosed ADHD using information from resting state MR experiments. Male right handed volunteers (infants with ages between 7 and 11 years old) were studied and compared with age matched controls. Wavelet analysis, which is a mathematical tool used to decompose time series into elementary constituents and detect hidden information, was applied here to the BOLD signal obtained from the cerebellum 8 region of all our volunteers. Statistical differences between the values of the a parameters of wavelet analysis was found and showed significant differences (p<0.02) between groups. This difference might help in the future to distinguish healthy from ADHD patients and therefore diagnose ADHD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A Bayesian Measurment Error Model for Misaligned Radiographic Data

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error in addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

All-optical control of charge transfer and interlayer excitons in transition metal dichalcogenide heterostructures

An all-optical approach to control interlayer charge transfer and interlayer exciton dynamics is demonstrated using transition metal dichalcogenide heterostructures of MoSe 2 /MoS 2 and MoSe 2 /WS 2 as examples. In the three-pulse pump-probe experiments, a control pulse injects photocarriers and produces an electric field due to the interlayer charge separation. A pump pulse excites new carriers and their dynamics under the influence of the control-injected carriers and field is time-resolved by measuring differential reflectance of a third probe pulse. In MoSe 2 /MoS 2 , the interlayer electron transfer time from MoSe 2 to MoS 2 decreases with increasing the control-injected carrier density and electric field. The dipole moment of the interlayer excitons is reduced by the control pulse, which can be utilized for ultrafast and all-optical control of interlayer excitons. The recombination of the interlayer excitons is enhanced by the control pulse, which increases the spatial overlap of the electron and hole wave functions. The effect of the control pulse on the interlayer excitons is confirmed in the MoSe 2 /WS 2 heterostructure, although its effect on the electron transfer time is not resolvable. Furthermore, these results reveal useful information to understand and control interlayer charge transfer dynamics and provide tools for ultrafast manipulation of electrons in van der Waals heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics

Three-dimensional (3D) micro-tomography (µ-CT) has proven to be an important imaging modality in industry and scientific domains. Understanding the properties of material structure and behavior has produced many scientific advances. An important component of the 3D µ-CT pipeline is image partitioning (or image segmentation), a step that is used to separate various phases or components in an image. Image partitioning schemes require specific rules for different scientific fields, but a common strategy consists of devising metrics to quantify performance and accuracy. The present article proposes a set of protocols to systematically analyze and compare the results of unsupervised classification methods used for segmentation of synchrotron-based data. Additionally, the proposed dataflow for Materials Segmentation and Metrics (MSM) provides 3D micro-tomography image segmentation algorithms, such as statistical region merging (SRM), k-means algorithm and parallel Markov random field (PMRF), while offering different metrics to evaluate segmentation quality, confidence and conformity with standards. Both experimental and synthetic data are assessed, illustrating quantitative results through the MSM dashboard, which can return sample information such as media porosity and permeability. The main contributions of this work are: (i) to deliver tools to improve material design and quality control; (ii) to provide datasets for benchmarking and reproducibility; (iii) to yield good practices in the absence of standards or ground-truth for ceramic composite analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗
DOE OSTI2014

Energy-Saving Melting and Revert Reduction Technology (E-SMARRT): Final Summary Report

Energy-Saving Melting and Revert Reduction Technology (E-SMARRT) is a balanced portfolio of R&D tasks that address energy-saving opportunities in the metalcasting industry. E-SMARRT was created to: • Improve important capabilities of castings • Reduce carbon footprint of the foundry industry • Develop new job opportunities in manufacturing • Significantly reduce metalcasting process energy consumption and includes R&D in the areas of: • Improvements in Melting Efficiency • Innovative Casting Processes for Yield Improvement/Revert Reduction • Instrumentation and Control Improvement • Material properties for Casting or Tooling Design Improvement The energy savings and process improvements developed under E-SMARRT have been made possible through the unique collaborative structure of the E-SMARRT partnership. The E-SMARRT team consisted of DOE’s Office of Industrial Technology, the three leading metalcasting technical associations in the U.S: the American Foundry Society; the North American Die Casting Association; and the Steel Founders’ Society of America; and SCRA Applied R&D, doing business as the Advanced Technology Institute (ATI), a recognized leader in distributed technology management. This team provided collaborative leadership to a complex industry composed of approximately 2,000 companies, 80% of which employ less than 100 people, and only 4% of which employ more than 250 people. Without collaboration, these new processes and technologies that enable energy efficiencies and environment-friendly improvements would have been slow to develop and had trouble obtaining a broad application. The E-SMARRT R&D tasks featured low-threshold energy efficiency improvements that are attractive to the domestic industry because they do not require major capital investment. The results of this portfolio of projects are significantly reducing metalcasting process energy consumption while improving the important capabilities of metalcastings. Through June 2014, the E-SMARRT program predicts an average annual estimated savings of 59 Trillion BTUs per year over a 10 year period through Advanced Melting Efficiencies and Innovative Casting Processes. Along with these energy savings, an estimated average annual estimate of CO2 reduction per year over a ten year period is 3.56 Million Metric Tons of Carbon Equivalent (MM TCE).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Phasor Simulator for Operator Training Project

Synchrophasor systems are being deployed in power systems throughout the North American Power Grid and there are plans to integrate this technology and its associated tools into Independent System Operator (ISO)/utility control room operations. A pre-requisite to using synchrophasor technologies in control rooms is for operators to obtain training and understand how to use this technology in real-time situations. The Phasor Simulator for Operator Training (PSOT) project objective was to develop, deploy and demonstrate a pre-commercial training simulator for operators on the use of this technology and to promote acceptance of the technology in utility and ISO/Regional Transmission Owner (RTO) control centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Fall 2016 Solicitation Projects Website Info

Spark-ignition engines are the backbone behind people transportation around the world. The efficiency of spark-ignition engines is limited in practice by variations between engine cycles and cylinders within an engine that result from the manufacturing processes/tolerances. These variations impact knock limits and dilution tolerance, which results in more conservative settings for design and calibration settings, such as compression ratio, valve timing, and exhaust gas recirculation rates. Engine variations also have a significant impact on emissions generation, which can have a secondary impact on efficiency. A deeper understanding of the relative importance of these variations and their interactions on the charge preparation process can guide future decisions on machining tolerances and control strategies. This project will develop simulation tools and methodology to include the effects of some key manufacturing tolerances and their impact on engine performance and emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

2017 NE-4 Nuclear Technologies Research and Development (NTRD) Achievements Report

Fiscal year (FY) 2017 initiated new and reestablished presidential and departmental nuclear energy priorities for the U.S. Department of Energy (DOE), Office of Nuclear Energy (DOE-NE) that will: • Support the Administration’s priorities to achieve U.S. energy dominance and economic prosperity through U.S. technology leadership • Support DOE-NE mission priorities and goals for the existing nuclear fleet, advanced reactor pipeline and national fuel cycle infrastructure • Focus on early stage research, and effective cooperation with industry, academia, and other government agencies • Propose investments to maintain and improve capabilities and infrastructure to conduct leading-edge science, research, and technology development. DOE-NE’s mission priorities will focus on the existing nuclear fleet, advanced reactor pipeline, and fuel cycle infrastructure. Therefore, the DOE Nuclear Technology Research and Development (NE-4) mission aligned to (1) support the research and development (R&D) of innovative reactor technologies that may offer improved safety, functionality, and affordability and (2) conduct research to reduce long-term technical barriers for advanced nuclear energy systems, including space fission systems. Key activities to execute this mission include: • To achieve the NE-4 mission priorities, two major programs with eight R&D campaigns are engaged in impactful research, development, demonstration, and deployment: Fuel Cycle Technologies (FCT) Program • Fuel Cycle Options Campaign evaluates complex fuel cycle options and provides performance metrics on various systems and scenarios to improve the knowledge of interdependencies between technologies and different systems. • Advanced Fuels Campaign performs science-based R&D on accident tolerant fuels in addition to advanced light-water reactor (LWR) fuel and transmutation fuel. • Joint Fuel Cycle Studies (JFCS) is a collaboration with the Republic of Korea to assess the feasibility and nonproliferation of electrochemical recycling to manage used fuel. • Material Recovery and Waste Form Development (MRWFD) Campaign researches advanced fuel cycle material recovery and waste management capabilities to improve fuel cycle performance with less processing and waste generation. • Material Protection, Control, and Accountability Technologies (MPACT) Program develops tools and capabilities to secure the next generation nuclear materials management and safeguards for nuclear fuel cycles. Advanced Reactor Technologies (ART) Program • Fast Reactors Campaign targets benefits in either resource utilization or waste management and possesses favorable features for small reactor applications and plutonium management. • Gas-Cooled Reactors Campaign seeks to raise the technological readiness of high temperature gas-cooled reactors (HTGRs) and other reactor concepts utilizing coated particle fuel, graphite, or helium coolant by performing high risk, enabling research and development that commercial developers are unable or unwilling to undertake in the current energy market. • ART Energy Conversion (EC) Project provides solutions to convert heat from an advanced reactor to useful products that support commercial application of the reactor designs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Prototype System for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and equipment out of service would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify the incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment that is being relied on to meet the requirements of the nuclear safety plan. In addition, Operations and the Outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently in outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This project will develop tools and strategies to minimize these interactions. This report describes a prototype tool designed to support plant personnel in controlling work during NPP outages to prevent unintended interactions. A software application was created to manage and display important configuration information and utilize natural language processing to access the impacts of upcoming procedures and work orders. Initial industry feedback is also presented.

99 GENERAL AND MISCELLANEOUS↗