Capturing design process information and rationale to support knowledge-based design and analysis integration

Issued as final reportUnited States. Dept. of Commerc

RT137 ITAP: SysML Building Blocks for Cost Modeling

SERC Sponsor Research Review, December 3, 201

-ilities Tradespace and Affordability Project – Phase 3

One of the key elements of the SERC’s research strategy is transforming the practice of systems engineering and associated management practices – “SE and Management Transformation (SEMT).” The Grand Challenge goal for SEMT is to transform the DoD community’s current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first, document-driven, point- solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise- oriented, hardware-software-human engineered, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08- D-0171 (Task Order 0031, RT 046)

Facilitating the Transition to Model-Based Acquisition

Presented March 11, 2020 at IEEE Aerospace Conference 2020.© IEEEOne major benefit offered by MBSE is the ability to formalize interactions between subsystems in the design process. This formalization eases the transfer of information between parties. The process of government acquisition is likewise characterized by information transfer: diverse requirements must be altered and tracked between the requesting, responding, and evaluating parties. Thus, it is a natural extension of MBSE is to apply it to the acquisition process. This paper demonstrates a set of tools and patterns developed during a surrogate simulation of an MBSE-enabled Request for Proposal between NAVAIR and a responding contractor. In particular, the tools presented were developed from the NAVAIR Systems Model viewpoint. This paper covers four tools developed in this surrogate pilot. The first analyzes the problem of requirement generation. While standards such as the OMG SysML are being adopted by MBSE practitioners, the model literacy of all stakeholders is unlikely and may never be fully guaranteed. Document generation tools, such as OpenMBEE have been developed for SysML software, which enable presentation of descriptive information about the model. This paper demonstrates modeling patterns and a tool that translates information from native-model form into a text-based format. The second and third tools presented assist in the acquirer’s source selection process. Making use of the patterns which generate the text requirements above, Evaluation and Estimation Models are presented, which can act directly on contractors’ responses. The Evaluation Model assists the verification process by ensuring numerical requirements are satisfied. The Estimation Model compares the contractors’ claimed values with historically expected values, to assist directing the source selection experts’ focus of examination. The fourth tool presented offers a method of extracting historical traceability for model elements. This aids the acquisition process by enabling digital signoff at any stage of the acquisition process. These four tools were applied in the surrogate acquisition process for a notional UAV, and a description of this case study is presented.NAVAIR/SERC RT170/RT195, Contract HQ0034-13-D-00

WRT-1006 Technical Report: Developing the Digital Engineering Competency Framework (DECF) – Phase 2

17 USC 105 interim-entered record; under review.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-19-D-003 (Task Order 0286).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-19-D-003 (Task Order 0286). U.S. Government affiliation is unstated in article tex

WRT-1006 Technical Report: Developing the Digital Engineering Competency Framework (DECF), Version 1.0

17 USC 105 interim-entered record; under review.Digital engineering is ‘‘an integrated digital approach that uses authoritative sources of systems’ data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. A DE ecosystem is an interconnected infrastructure, environment, and methodology that enables the exchange of digital artifacts from an authoritative source of truth.”1 Digital transformation is fundamentally changing the way acquisition and engineering are per-formed across a wide range of government agencies, industries, and academia and is characterized by the integration of digital technology into all areas of a business, changing fundamental operations and how results are delivered in terms of new value to customers. It includes cultural change centered on alignment across leadership, strategy, customers, operations, and workforce evolution.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-004 (Task Order 0082).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-004 (Task Order 0082). U.S. Government affiliation is unstated in article tex

System Qualities Ontology, Tradespace and Affordability (SQOTA) Project – Phase 4

This task was proposed and established as a result of a pair of 2012 workshops sponsored by the DoD Engineered Resilient Systems technology priority area and by the SERC. The workshops focused on how best to strengthen DoD’s capabilities in dealing with its systems’ non-functional requirements, often also called system qualities, properties, levels of service, and –ilities. The term –ilities was often used during the workshops, and became the title of the resulting SERC research task: “ilities Tradespace and Affordability Project (iTAP).” As the project progressed, the term “ilities” often became a source of confusion, as in “Do your results include considerations of safety, security, resilience, etc., which don’t have “ility” in their names?” Also, as our ontology, methods, processes, and tools became of interest across the DoD and across international and standards communities, we found that the term “System Qualities” was most often used. As a result, we are changing the name of the project to “System Qualities Ontology, Tradespace, and Affordability (SQOTA).” Some of this year’s university reports still refer to the project as “iTAP.”This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-13-D-0004

Belle II Technical Design Report

The Belle detector at the KEKB electron-positron collider has collected almost 1 billion Y(4S) events in its decade of operation. Super-KEKB, an upgrade of KEKB is under construction, to increase the luminosity by two orders of magnitude during a three-year shutdown, with an ultimate goal of 8E35 /cm^2 /s luminosity. To exploit the increased luminosity, an upgrade of the Belle detector has been proposed. A new international collaboration Belle-II, is being formed. The Technical Design Report presents physics motivation, basic methods of the accelerator upgrade, as well as key improvements of the detector.Comment: Edited by: Z. Dole\v{z}al and S. Un

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049