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One of the most ubiquitous types of decomposers in nature, brown rot fungi, has lacked robust genetic tools by which to manipulate genes and understand its biology. Brown rot fungi are primary decomposers in northern forests helping recycle the encased carbons in trees back to ecosystem.
A Test/Score/Report capability is currently being developed for the Transportable Payload Operations Control Center (TPOCC) Advanced Spacecraft Simulator (TASS) system which will automate testing of the Goddard Space Flight Center (GSFC) Payload Operations Control Center (POCC) and Mission Operations Center (MOC) software in three areas: telemetry decommutation, spacecraft command processing, and spacecraft memory load and dump processing. Automated computer control of the acceptance test process is one of the primary goals of a test team. With the proper simulation tools and user interface, the task of acceptance testing, regression testing, and repeatability of specific test procedures of a ground data system can be a simpler task. Ideally, the goal for complete automation would be to plug the operational deliverable into the simulator, press the start button, execute the test procedure, accumulate and analyze the data, score the results, and report the results to the test team along with a go/no recommendation to the test team. In practice, this may not be possible because of inadequate test tools, pressures of schedules, limited resources, etc. Most tests are accomplished using a certain degree of automation and test procedures that are labor intensive. This paper discusses some simulation techniques that can improve the automation of the test process. The TASS system tests the POCC/MOC software and provides a score based on the test results. The TASS system displays statistics on the success of the POCC/MOC system processing in each of the three areas as well as event messages pertaining to the Test/Score/Report processing. The TASS system also provides formatted reports documenting each step performed during the tests and the results of each step. A prototype of the Test/Score/Report capability is available and currently being used to test some POCC/MOC software deliveries. When this capability is fully operational it should greatly reduce the time necessary to test a POCC/MOC software delivery, as well as improve the quality of the test process.
The National Renewable Energy Laboratory (NREL) and its project partners have developed the novel Solar Automated Permit Processing plus (SolarAPP+) software platform that provides a flexible, web-based PV-permitting tool for residential systems that can be integrated with existing and complementary software platforms. The main objective of this research is to analyze the implementation of SolarAPP+. Analysis was conducted by identifying the benefits, tradeoffs, and overall performance of SolarAPP+, including achieving its goals of delivering automated, code compliant systems, influencing permitting cycle times, and improving application submittals and/or inspection performance. The NREL team published the results of this analysis in annual SolarAPP+ Performance Review technical reports.
This report describes the credibility activities undertaken in support of Gemma code development in FY20, which include Verification & Validation (V&V), Uncertainty Quantification (UQ), and Credibility process application. The main goal of these activities is to establish capabilities and process frameworks that can be more broadly applied to new and more advanced problems as the Gemma code development effort matures. This will provide Gemma developers and analysts with the tools needed to generate credibility evidence in support of Gemma predictions for future use cases. The FY20 Gemma V&V/UQ/Credibility activities described in this report include experimental uncertainty analysis, the development and use of methods for optimal design of computer experiments, and the development of a framework for validation. These initial activities supported the development of broader credibility planning for Gemma that continued into FY21.
This paper presents a final report on Optical Fabrication and Measurement AXAF (Advanced X-Ray Astrophysics Facility) and CIRS (Composite Infrared Spectrometer) from July 12, 1994 to August 16, 1996.. This paper includes specific tasks to be performed. The tasks are as follows: 1) Preparation and Characterization of Zerodur Glass Samples; 2) Develop and Fabricate AXAF and CIRS Metrology Tooling; 3) Update AXAF Technical Data Base; and 4) Perform Fabrication Related Metrology Tasks for CIRS. This paper also includes final activities from the July, 1996 report to August 1996.
Previous JPL ground systems have been designed with the Ground Data System (GDS) engineer in mind. The focus on these systems has been on packaging and delivery of low level information (frames, packets, telemetry values) to the end user. It was not that long ago when project teams would be huddled over a workstation, examining crude displays of telemetry bits organized in various ways, trying to determine the status of a spacecraft. Understanding the data often required additional levels of GDS expertise, or worse, transformation of the raw data into alternative formats followed by ingestion into other tools so that the data became meaningful. The primary focus was often to answer these types of questions: "Why did this particular frame fail Reed-Solomon decode? Why did this packet get marked as invalid? Why am I missing a block of telemetry from my query?" -- which are completely valid questions to ask from a GDS Engineer's point of view, and large families of tools have been designed to help answer these questions. But these are not the questions that most users care about - which are more like: "Why is the battery state of charge trending down? Show me a summary image report for the last traverse to the target. Show me a data accountability summary for the last DSN pass." Answers to these questions, which are what users are looking for, requires a higher level of abstraction and supporting tools than mining through ones and zeros. JPL has created a next generation capability called the Mission Data Processing and Control System (MPCS) which is designed to support this higher level of abstraction by providing customizable views of the ground system combining collections of lower level information into more meaningful ways. Instead of examining frames, packets, and individual telemetry data points -- MPCS is capable of providing comprehensive summary reports, product status, overall flight/ground event status, as well as payload health summaries. Based on these higher level views, end users can make tactical or strategic decisions, or drop into detailed analysis as needed. System designers need to continue building systems that support low level GDS troubleshooting - but the basic design of a GDS should be geared towards what end users actually need to see. This paper will describe the capabilities of MPCS that directly support these higher levels of abstraction, and which are being used today in missions such as the Mars Science Laboratory and other NASA missions.
This report describes work supported by a post-launch grant (NCC 2-679) that originally covered the period from 1 January 1990 through 31 December 1992. This was extended an additional nine months at no cost until 30 September 1993, and once more until to 30 November 93. A final report on the effort from 1 January 1990 through 30 November 1993 (anticipated) is provided following the background discussion. Tasks required during the post launch period are briefly as follows: (1) attend PSG (Project Science Group) meetings; (2) support in-flight checkouts; maintain and keep safe the spare instrument and GSE (Ground Support Equipment); (3) organize and maintain documentation; (4) finish calibration measurements, documentation, and analysis; (5) characterize and diagnose instrument anomalies; (6) develop descent data analysis tools; and (7) science data analysis and publication. The following sections provide background information on the NFR instrument followed by the complete progress report.
As Software Bill of Materials (SBOM) adoption efforts mature, SBOM sharing continues to occur, but no single solution or set of solutions have become ubiquitous. The purpose of this report is to enumerate and describe the different parties and phases of the SBOM sharing lifecycle and assist readers in choosing suitable SBOM sharing solutions based on the amount of time, resources, subject-matter expertise, effort, and access to tooling that is available to the reader to implement a phase of the SBOM sharing lifecycle. The SBOM sharing lifecycle consists of the Discovery, Access, and Transport of an SBOM and this report details these individual phases and how an SBOM goes from author to the consumer. This report also details how potential enrichment activities may be performed on an SBOM to create a new product before or after it has been shared. The concept of a sophistication classification for SBOM sharing solutions is concurrently introduced with a focus on the inclusion or lack of certain features and effort associated with their implementation. Examples of low, medium, and high-sophistication solutions are provided; however, these examples and associated categorizations should not be seen as a qualitative judgment meant to push the reader towards a particular adoption strategy since sharing solutions are chosen based on the unique needs of the user. This report does recommend the SBOM community consider how to make current and future sharing solutions interoperable with each other as well as more automated methods to facilitate sharing and broader SBOM adoption. This report also highlights an SBOM sharing survey results obtained from interviews with stakeholders to understand the current SBOM sharing landscape. The categorized results of the survey suggest that SBOMs are currently transported directly to the receiver through email or similar informal communication mechanisms or alternatively the SBOM resides on a repository available to consumers. In addition to these transport methods, this report captures industry efforts to create private sharing solutions and services that can store and transport enrichment data and may use higher sophistication features that are cloud-based or using distributed ledger technologies.
This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an effort to filter out high frequency characteristics. The fourth method removes the presumed system excitation and its harmonics in order to investigate the effects of the excitation on the modeling process. The fifth method is an attempt to apply constrained RID to obtain better transfer functions through more accurate modeling over certain frequency ranges. Section 4 presents some new C main files which were created to round out the functionality of the existing SSME transfer function modeling code. It is now possible to go from time data to transfer function models using only the C codes; it is not necessary to rely on external software. The new C main files and instructions for their use are included. Section 5 presents current and future enhancements to the XPLOT graphics program which was delivered with the initial software. Several new features which have been added to the program are detailed in the first part of this section. The remainder of Section 5 then lists some possible features which may be added in the future. Section 6 contains the conclusion section of this report. Section 6.1 is an overview of the work including a summary and observations relating to finding transfer functions with the SSME code. Section 6.2 contains information relating to future work on the project.
Recording changes in beam transverse positions and longitudinal phase reported by Beam Position Monitors (BPMs) in response to a beam deflection by an upstream dipole corrector or RF cavity phase (orbit response) is a powerful tool for analysis of accelerator optics and assisting with machine tuning. In Fermilab Linac, orbit responses were recorded by oscillating the corrector currents and cavity phases in a sinusoidal manner parasitically during regular operation, simultaneously oscillating up to 19 correctors and 7 cavities at distinct frequencies, providing faster, drift-resistant measurements through frequency-domain analysis. This report describes the technique, including error estimations and consistency checks and shows examples of the measurements.
On October 7-8, 2024, the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) and the National Renewable Energy Laboratory hosted an in-person workshop focused on research needs and strategies for community benefit mechanisms (CBMs) used in the deployment of renewable energy infrastructure. Community benefit mechanisms (such as community benefit agreements, funds, and donations) are used to provide increased benefits and/or mitigate negative impacts of energy development for the communities that are impacted. The workshop aimed to assess the current state of knowledge, tools, practices, and lessons learned, as well as to identify research and other work needed to improve the impact and effective implementation of CBMs. This report describes the purpose and structure of the workshop and summarizes key themes, questions, issues, and ideas that arose from the workshop.
The goal of the project was to develop the necessary analysis tools for a feasibility study of a cable suspended robot system for examining the space shuttle orbiter payload bay radiators These tools were developed to address design issues such as workspace size, tension requirements on the cable, the necessary accuracy and resolution requirements and the stiffness and movement requirements of the system. This report describes the mathematical models for studying the inverse kinematics, statics, and stiffness of the robot. Each model is described by a matrix. The manipulator Jacobian was also related to the stiffness matrix, which characterized the stiffness of the system. Analysis tools were then developed based on the singular value decomposition (SVD) of the corresponding matrices. It was demonstrated how the SVD can be used to quantify the robot's performance and to provide insight into different design issues.
Additive manufacturing of freeform structures containing multiple materials with deterministic spatial arrangement and interactions remains a challenge for most 3D printing processes, due to complex fabrication tool requirements and limitations in printability of some material classes. Here, in this paper, a versatile method is reported to produce architected composites using the concept of cellular fluidics, in which lattices of unit cells are used as templating scaffolds to guide flowable infill materials in a programmed spatial pattern, upon which they are cured in place to produce a deterministically ordered multimaterial solid. The lattice design relies on the unit cell size, type, strut diameter, surface wetting, and distribution of cellular structures to control liquid flow and retention. Individual unit cells are tuned to achieve reliable infilling and combined into higher-order architectures to achieve multiscale composite materials with disparate mechanical properties, including those considered non-printable. Lattice design considerations for leveraging capillary phenomena and demonstrate several methods of patterning polymers in 3D-printed cellular fluidic structures are presented. The concept of tuning the compressive response of an architected composite using a flexible-elastomer as the lattice and a stiff-epoxy as the infill material is illustrated.
The present study documents an automated approach to performing elemental analysis on a large group uranium ore concentrate (UOC) samples. In this work, 17 UOC samples, 2 quality control samples, and 26 process blanks were purified sequentially through a single 500 μL Uranium and TEtra Valent Actinides (UTEVA®) column. For each sample, the trace elemental impurities were separated from its dissolved uranium matrix on the UTEVA column and collected for analysis by inductively coupled plasma – optical emission spectroscopy / triple quadrupole mass spectrometry (ICP-OES/TQMS). The UTEVA column was subsequently regenerated prior to separation of the following sample. The column was efficiently regenerated, for each UOC, even after processing ~50 mg of uranium, cumulatively. The validity of the method was established by determining the trace impurities of two quality control uranium reference samples (CRM 124–1 and CUP-2). The current trace element measurements from the 17 UOC samples were compared to previously reported values from an interlaboratory comparison exercise, when available. The methodology employed here produces trace elemental analysis with excellent correlation to the previously reported data for many of the elements / samples, particularly when viewed through the context of existing geochemical comparisons tools (e.g. chondrite normalized variation plots).
We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.
Here, we report nuclear science and engineering is a field increasingly dominated by computational studies resulting from increasingly powerful computational tools. As a result, analytical studies, which previously pioneered nuclear engineering, are increasingly viewed as secondary or unnecessary. However, analytical solutions to reduced-fidelity models can provide important information concerning the underlying physics of a problem and aid in guiding computational studies. Similarly, there is increased interest in sensitivity analysis studies. These studies commonly use computational tools. However, providing a complementary sensitivity study of relevant analytical models can lead to a deeper analysis of a problem. This work provides the analytical sensitivity analysis of the one-dimensional (1D) cylindrical mono-energetic neutron diffusion equation using the forward sensitivity analysis procedure (FSAP) developed by Cacuci. Further, these results are applied to a reduced-fidelity model of a spent nuclear fuel cask, demonstrating how computational analysis might be improved with a complementary analytic sensitivity analysis.
CATCH CLI focuses on gathering telemetry data, storing it in the Neo4j database, querying for Mitre ATT&CK patterns, and creating STIX 2.1 reports. Key Components: Analysis Modules: Analyze data to detect attack patterns. GoSTOTS Collection Engines: Collect telemetry data. These tools can be used together or individually. Analysis modules rely on data from specific engines to identify attack patterns. Source Code Organization: Engines: CATCH/catch/cmd/collection Modules: CATCH/catch/cmd/analysis CGUI Overview CATCH Graphical User Interface (CGUI) offers a graphical shell to execute CATCH CLI, allowing easy editing of: Analysis Modules Database configurations Profiles (collection and device settings) Neo4j Overview Neo4j is a graph database using the Cypher query language, storing data in JSON. It seamlessly integrates with STIX 2.1 data for: Data Submission: CATCH Collection Engines Data Querying: Analysis Modules CATCH modifies STIX 2.1 data for Neo4j submission and reverts it back during querying. STIG Overview Structured Threat Intelligence Graph (STIG) is a tool for creating, editing, querying, analyzing, and visualizing threat intelligence using STIX 2.1 and storing data in Neo4j. Usage Tools can be run: Manually (CLI): Refer to CATCH documentation User Interface: Run ./cgui/CGUI or go run ./cgui/ Additional Information Logging System: Detailed in the config documentation Further Documentation: Available for CATCH and CGUI
A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.