The IEEE draft standard, P3388, titled “Standard for the Performance Assessment of Industrial Wireless Systems,” has been submitted for IEEE Standards Association balloting. Under the leadership of NIST’s Rick Candell, the P3388 working group addresses several performance measurement objectives. This standard establishes a functional model for radio frequency (RF) industrial wireless performance degradation factors (referred to as “aggressors”). Additionally, it provides a reference test architecture for evaluating the performance of industrial wireless systems. Transparency is a key focus, with a well-defined assessment process for test planning, evaluation, and reporting. Furthermore, the standard includes instructions for establishing profiles to tailor the assessment process for specific industries, applications, and scenarios. The 3388 standard encompasses all wireless networks used in industrial settings, where reliability and latency may significantly impact operational functionality and safety. The standard addresses performance degradation factors arising from both physical and electromagnetic forms of wireless signal degradation. This milestone marks a major step in making wireless technology a reliable mode of communications in industrial environments.
On February 28-29, 2024, the NIST Automated Vehicles team, representing multiple NIST laboratories, visited the Virginia Tech Transportation Institute (VTTI) site in Blacksburg, VA. The program for the two-day meeting included presentations, collaboration discussions, and tours of VTTI’s Smart Road testing facility, testbeds, and automated vehicle (AV) research. The event was organized by NIST’s Ed Griffor and VTTI’s Mac McCall, and included in-person participation by NIST AV program/project leads and team members, including Zeid Kootbally, Apostol Vassilev, David Wollman, Thomas Roth, Chunmei Liu, and Omar Aboul-Enein.
The NIST and VTTI teams provided summaries of their respective research activities and capabilities, covering key topics such as vehicle testing practices and safety procedures, Artificial Intelligence, perception systems, naturalistic driving studies, data/hardware systems, AV communications, co-simulation, and overall system interactions. After an extensive facilities tour, the teams had in-depth discussions on existing and potential collaborative research and opportunities for alignment of current and future goals.
Additional NIST participants included Wenqi Guo, Eugene Song, Mahima Arora, Ninad Harishchandrakar, Usman Fiaz, Hadhoum Hajjaj, Giray Oral, Munawar Hasan, Pavel Piliptchak, Colin Shaefer, and Thoshitha Gamage.
What city infrastructure could be used or developed to support automated vehicles (AVs) is a recent topic of discussion in the AV research community. NIST researcher Dr. Edward Griffor organized a half-day session on this topic of Digital Infrastructure at the NIST Automated Vehicles Workshop in September 2023, which featured keynote speaker Ed Straub, Vice President of Land Systems for SAE Industry Technologies Consortia and Director of the Office of Automation, SAE International.
Ed Straub proposed to the SAE On-Road Automated Driving (ORAD) Committee, and it has created, an Exploratory Working Group to develop the concept of an AV ‘Usage Specification’. An initial scoping meeting was held on February 8, 2024, with stakeholders from NIST, SAE, and AV developers and manufacturers. This activity will benefit both AV developers and Infrastructure Owners and Operators (IOOs), including providing better understanding of the purpose and use of AVs and the potential impact on the design of roadways, intersections, traffic controls, and vehicle and infrastructure technologies.
Although many foundational concepts of driving automation have been described in SAE standards, including J3016 and others, the idea of vehicle use or purpose has received little attention to date. But the “intended use” of a vehicle is an important consideration that bridges vehicle technologies with where and how people use them. This connects the technologies to transportation and innovation stakeholders, including developers and regulators and consumers.
The proposed SAE Exploratory Working Group is anticipated to:
further develop the concept of “usage specification” that captures vehicle automation usage or purpose, automation level, and operational constraints;
publish results in new SAE standards or revisions of existing SAE standards; and
implement the results in an integrated vehicle-infrastructure taxonomy as a widely accessible “database” to align the development of future standards for vehicles and infrastructure.
At the 2023 International Conference on System Reliability and Safety (ICSRS) in Bologna, Italy, NIST researcher Mehdi Dadfarnia presented research findings that aim to help manufacturers understand the risks and benefits of integrating AI-based condition monitoring systems with their maintenance practices. The research findings make use of the NIST-developed, open-source SimPROCESD software, which is a Python-based discrete-event simulator for multistage manufacturing and equipment maintenance. This conference attracts experts that showcase cutting edge research in risk analysis and reliability engineering.
Dadfarnia’s presentation described the ability to:
Compare different AI-based condition monitoring algorithms that enable the same maintenance policy on their algorithm-level metrics (such as accuracy or precision) and ability to improve a manufacturer’s key performance indicator (such as production quantity or product quality).
Compare different maintenance policies, including inspection-based and condition-based policies, on their ability to improve a manufacturer’s key performance indicator.
Compare the effectiveness of maintenance policies across various manufacturing configurations and shopfloor setups.
This talk presented work from a broader effort in NIST’s Industrial Artificial Intelligence Management and Metrology project, which develops domain-specific tools and methods to improve the effective use of AI systems and tools in industrial applications and to understand their financial and engineering risks and benefits.
NIST’s Systems Analysis Integration (SAI) project was invited to present its research to the NASA Jet Propulsion Laboratory (JPL) Systems Engineering Solutions Group and members of the Open Model Based Engineering Environment project (OpenMBEE), an open-source effort led by JPL and Boeing to deliver major improvements in systems engineering software. The SAI project is part of the Smart Connected Manufacturing Systems Group, led by Allison Barnard Feeney. The project increases efficiency of engineering processes by integrating a variety of automated analyses with the Systems Modeling Language (SysML), the most widely used modeling language for systems engineering, in order to reliably share system specifications and analysis results among project contributors. JPL and NIST have collaborated on systems analysis integration for over ten years, contributing research results to standards development at the Object Management Group (OMG), which publishes SysML.
NIST SAI staff presented and discussed several areas of analysis integration over 2 days at JPL:
Charles Manion showed his work on expanding capabilities of the SysML Extension for Physical Interaction and Signal Flow Simulation (SysPhS), a standard published by OMG for modeling time-based (1D) physical and signal behavior in complex systems designs, as well as translating models to two well-known 1D simulation platforms. He covered three new SysPhS physical component libraries, along with examples applying them to manufacturing system modeling. Manion automatically translated and simulated the examples on 1D simulation platforms using software developed by NIST’s Raphael Barbau.
Raphael Barbau reported on his extension of SysML for logistics modeling and analysis (SysLMA), soon to be submitted for standardization at OMG. SysLMA describes logistics systems at multiple levels of detail, and defines mappings to widely used analysis platforms for multi-commodity flow optimization, queuing analysis, and discrete event simulation. Barbau demonstrated his software for automatically translating SysLMA to analysis platforms, performing analysis, and producing results as feedback to system design.
Conrad Bock, SAI project leader, outlined his research on adapting SysML behavior models for logical analysis, Ontological Behavior Modeling (OBM), to give a mathematical foundation for expressing system behavior. It combines temporal interval relations and SysML’s capabilities for assembling systems to produce an engineering-friendly way of constructing behavior models that are logically grounded. This significantly reduces the complication of SysML behavior modeling, making it easier to learn and build tool support. It is included an upcoming major update to SysML by OMG.
Barbau also described his software for verifying OBM by automatic translation to Satisfiability Modulo Theory (SMT) solvers, via a widely used file format for stating these kind of logical problems. He demonstrated it on OBM examples, translating and solving them on an open-source logical solver to produce valid executions of the behaviors or to show they could not be executed properly according to the behavior models.
Jeremy Doerr of the Georgia Tech Research Institute covered related work developed under a NIST grant translating OBM to Alloy Analyzer, a textual language and solver for Boolean Satisfiability (SAT) problems. He described the language and how to translate OBM examples similar to Barbau’s above.
Bock concluded by reviewing his research on four dimensional systems requirements modeling, an enhancement of OBM to specify behavior of systems over time and space in an integrated framework. It is also included the upcoming major update to SysML, enabling spatial requirements to be modeled without initially committing to specific shapes, then later refining them topologically and geometrically.
JPL, Boeing, and other attendees provided feedback on the presentations and initiated plans for more interaction and collaboration.
NIST published Physical Component Libraries for SysPhS Modeling and Simulation in Manufacturing, a NIST interagency report (NIST IR 8490) by Charlie Manion, Conrad Bock, and Raphael Barbau that significantly expands the capabilities of the SysML Extension for Physical Interaction and Signal Flow Simulation (SysPhS), a standard published by the Object Management Group (OMG) for modeling time-based (1D) physical and signal behavior in complex systems designs, as well as translating models to two well-known 1D simulation platforms that give same results on both platforms. This kind of modeling and simulation is applicable to many kinds of physical interaction (such as mechanical, electrical, and so on) as well as communication of numeric and boolean signals, though current SysPhS physical component libraries only utilize electrical interaction. SysPhS extends OMG's Systems Modeling Language (SysML), the most widely used standard for systems engineering information modeling, and which is widely implemented by major SysML tool vendors.
The report augments SysPhS physical component libraries for
Translational mechanics: Includes translational inertia, springs, and dampers and other components that interact via linear momentum.
Rotational mechanics: Rotational analogs of the translational components above, which interact via angular momentum.
Heat transfer: Includes conduction, convection, and radiation, which interact via entropy.
Models built from these libraries translate to simulation platforms in the standard way, giving the same results on both platforms. The report demonstrates this with three examples of manufacturing system models using these libraries:
Weight compensating robot: collaborates with people to handle heavy objects, such as positioning a large tool during manufacturing or guiding an object through a complex path during assembly, by compensating for its weight.
Fused deposition modeling: melts a plastic filament in an extruder and deposits it on a surface, layer by layer, to make three dimensional shapes, used by most 3D printers.
Polishing machine: moves an abrasive tool (rotary or belt) over a part while applying a constant normal force to it.
The above examples employ the new physical component libraries to model physical structure and behavior, as well the current SysPhS signal libraries to control them. The report gives results of translating to two simulation platforms using software developed by NIST’s Raphael Barbau, showing they produce similar results.
Manion presented the new libraries to OMG for future updates to SysPhS, as well as to the Aerospace Corporation for application to space systems. They are also being used in ongoing work with Boeing to expand SysPhS thermal capabilities to fluid flow. The work is part of NIST’s Systems Analysis Integration (SAI) project, which increases the efficiency of engineering processes by integrating a variety of engineering analyses with SysML, enabling engineers of all kinds to reliably share information and results with each other.
In January 2024, NIST researchers Allison Barnard Feeney and Rosemary Astheimer worked with Ben Urick (nVariate) and Thomas Thurman (TRThurman Consulting) to implement a hybrid boundary-representation (b-rep) modeling capability in ISO 10303 Product data representation and exchange, commonly known as STEP, a widely adopted standard for CAD/CAE and PDM data exchange, system integration, visualization, and long-term preservation of product information.
Hybrid b-rep modeling is a recent capability in CAD systems that offers formal integration of multiple sources and types of geometry into a single b-rep geometric model. These tools allow engineers to include facet geometry from the proliferation of applications producing facet data (topology-optimization, 3D scanning, reverse-engineering, etc.) with precise geometry in their 3D model and edit seamlessly, without the need for conversion. STEP hybrid b-rep modeling data structures support mappings to Polyhedral B-reps™ (Dassault Systèmes), Convergent B-reps™ (Siemens), Mixed Modeling (PTC onshape), etc. Facet data is defined by triangular meshes to approximate surfaces and is is best suited for digital mock-ups, gaming and animation. Precise or explicit geometry b-rep models are defined mathematically and represent highly accurate, closed (solid) volumes used in scenarios where high precision is needed, such as 3D modeling for engineering analysis, manufacturing, and inspection.
The foundation of the STEP representation is an explicitly defined topological model, a face-edge-vertex structure or equivalent, b-rep solid model. In contrast to traditional b-rep models where the referenced geometry must be of the same type of geometric representation item, the hybrid topological model relaxes that constraint and is agnostic to subtypes of geometric representation item and topological representation item. The new hybrid b-rep model:
is consistent with geometric models and geometric model elements in ISO 10303-42 Geometric and topological modeling;
is aligned with ISO 23952 Quality information frameworkhybrid geometric model; and
supports modeling requirements for Isogeometric Analysis (IGA).
A planned extension to STEP hybrid b-rep modeling will support multiple sets of geometric references (in parallel) for a single b-rep topological model. This capability will enable multiple geometric digital twins of a product (engineering design, as-manufactured, as-inspected, for example) to be linked to the same topology.
The work was done under Working Group 12 STEP product modeling and resources, Team 1 Geometry and Topology (WG12/T1) of ISO Technical Committee 184 Automation Systems and Integration, Sub Committee 4 Industrial Data (ISO/TC 184/SC 4). This new capability is a common resource for any STEP application protocol that includes geometric modeling. It will appear first in ISO 10303-242 edition 4, Managed model-based 3D engineering, under Draft International Standard ballot this spring.
NIST is hosting the Named Data Networking (NDN) Community Meeting 2024 as a hybrid meeting on March 6-7, 2024. NDNComm provides a community forum to discuss the state of NDN protocols, software, testbed, and its application to various network environments. Panel topics planned for this year’s program include NDN open-source ecosystem, NDN for decentralized applications, and NDN-based network security framework. While in-person registration has closed, virtual registration is STILL AVAILABLE through the event page at https://www.nist.gov/news-events/events/ndncomm2024. We hope that you can join us this week!
