Results for “Consequence Management” — Page 6

NASA NTRS2001

Reliability of Fault Tolerant Control Systems

This paper reports Part I of a two part effort, that is intended to delineate the relationship between reliability and fault tolerant control in a quantitative manner. Reliability analysis of fault-tolerant control systems is performed using Markov models. Reliability properties, peculiar to fault-tolerant control systems are emphasized. As a consequence, coverage of failures through redundancy management can be severely limited. It is shown that in the early life of a syi1ein composed of highly reliable subsystems, the reliability of the overall system is affine with respect to coverage, and inadequate coverage induces dominant single point failures. The utility of some existing software tools for assessing the reliability of fault tolerant control systems is also discussed. Coverage modeling is attempted in Part II in a way that captures its dependence on the control performance and on the diagnostic resolution.

Wu, N. Eva↗

NASA NTRS2006

LOX, GOX and Pressure Relief

Oxygen relief systems present a serious fire hazard risk with often severe consequences. This presentation offers a risk management solution strategy which encourages minimizing ignition hazards, maximizing best materials, and utilizing good practices. Additionally, the relief system should be designed for cleanability and ballistic flow. The use of the right metals, softgoods, and lubricants, along with the best assembly techniques, is stressed. Materials should also be tested if data is not available and a full hazard analysis should be conducted in an effort to minimize risk and harm.

McLeod, Ken↗

NASA NTRSDate not supplied

Investigation of Intelligent Resource Management for Aviation Communications

The emergence of new aerial vehicles into the airspace as part of new initiatives, such as Advanced Air Mobility (AAM), will place growing demand for spectrum resources to support airspace operations. The traditional approach of using fixed channel allocations within standard service volumes will not allow for dynamic and efficient distribution of resources based on airspace demand; consequently, a new approach to aviation spectrum management will be required to meet the anticipated needs of airspace users. The National Aeronautics and Space Administration (NASA) is investigating the application of advanced concepts to implement a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the quality of service prescribed by aeronautical standards. This technical investigation evaluates the dynamic assignment of resources for both air-ground and air-air communication links applicable to both the emerging AAM initiative as well as the existing air traffic management system. The performance of the proposed spectrum management concepts will be evaluated using a custom modeling and simulation capability that is currently under development. The implementation of these approaches is anticipated to facilitate increased spectrum utilization efficiency and enhanced airspace capacity, which will better serve the needs of future applications.

Aeronautics↗

NASA NTRSDate not supplied

Investigation of Intelligent Resource Management for Aviation Communications

The emergence of new aerial vehicles into the airspace as part of new initiatives, such as Advanced Air Mobility (AAM), will place growing demand for spectrum resources to support airspace operations. The traditional approach of using fixed channel allocations within standard service volumes will not allow for dynamic and efficient distribution of resources based on airspace demand; consequently, a new approach to aviation spectrum management will be required to meet the anticipated needs of airspace users. The National Aeronautics and Space Administration (NASA) is investigating the application of advanced concepts to implement a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the quality of service prescribed by aeronautical standards. This technical investigation evaluates the dynamic assignment of resources for both air-ground and air-air communication links applicable to both the emerging AAM initiative as well as the existing air traffic management system. The performance of the proposed spectrum management concepts will be evaluated using a custom modeling and simulation capability that is currently under development. The implementation of these approaches is anticipated to facilitate increased spectrum utilization efficiency and enhanced airspace capacity, which will better serve the needs of future applications.

Eric Knoblock↗

NASA NTRS1997

An Automated Method for Identifying Inconsistencies within Diagrammatic Software Requirements Specifications

The development of large-scale, composite software in a geographically distributed environment is an evolutionary process. Often, in such evolving systems, striving for consistency is complicated by many factors, because development participants have various locations, skills, responsibilities, roles, opinions, languages, terminology and different degrees of abstraction they employ. This naturally leads to many partial specifications or viewpoints. These multiple views on the system being developed usually overlap. From another aspect, these multiple views give rise to the potential for inconsistency. Existing CASE tools do not efficiently manage inconsistencies in distributed development environment for a large-scale project. Based on the ViewPoints framework the WHERE (Web-Based Hypertext Environment for requirements Evolution) toolkit aims to tackle inconsistency management issues within geographically distributed software development projects. Consequently, WHERE project helps make more robust software and support software assurance process. The long term goal of WHERE tools aims to the inconsistency analysis and management in requirements specifications. A framework based on Graph Grammar theory and TCMJAVA toolkit is proposed to detect inconsistencies among viewpoints. This systematic approach uses three basic operations (UNION, DIFFERENCE, INTERSECTION) to study the static behaviors of graphic and tabular notations. From these operations, subgraphs Query, Selection, Merge, Replacement operations can be derived. This approach uses graph PRODUCTIONS (rewriting rules) to study the dynamic transformations of graphs. We discuss the feasibility of implementation these operations. Also, We present the process of porting original TCM (Toolkit for Conceptual Modeling) project from C++ to Java programming language in this thesis. A scenario based on NASA International Space Station Specification is discussed to show the applicability of our approach. Finally, conclusion and future work about inconsistency management issues in WHERE project will be summarized.

Zhang, Zhong↗

NASA NTRSDate not supplied

Lessons Learned With Risk Management: A Systems Engineer's Perspective

Risk management is a communications device that, when executed as an essential task, enables systems engineering to effectively balance risk across the project. Developing and baselining risks is an essential continuous task to ensure top project concerns both from bottom up and top down are being mitigated. Risk management provides the opportunity to avoid the consequence of the risk when mitigation steps start early enough. Just discussing risk with all the project flight elements during development, even if no risks are open, provides an excellent communication opportunity between systems engineering and those elements, ensuring concerns and worries have a platform for discussion. A well-managed risk identification process will identify concerns that are serious but not being clearly communicated, and it will enable mitigation of those potential problems before they cause a failure. Effective risk management requires considerable time and effort, but that effort will save time and money across the development. Risk management must be frequent enough to be useful and in depth enough to bring out emerging issues. It also requires a trusting relationship between the lead systems engineer and element and/or subsystem leads. The discussions need to be with the right number of individuals (typically a handful) and the right duration in time (typically an hour a month). Outside of these risk working groups, there is a formal management process to input, status, and disposition risks, and a monthly Risk Management Board meeting where key project stakeholders are informed. This paper provides good guidance on effective risk management from a systems engineering perspective and provides project lessons learned from the NASA spaceflight missions NICER, Landsat 9, LRO, and OSIRIS-REx to demonstrate the effectiveness of risk management.

Lessons Learned↗

NASA NTRSDate not supplied

Lessons Learned With Risk Management: A Systems Engineer’s Perspective

Risk management is a communications device that, when executed as an essential task, enables systems engineering to effectively balance risk across the project. Developing and baselining risks is an essential continuous task to ensure top project concerns both from bottom up and top down are being mitigated. Risk management provides the opportunity to avoid the consequence of the risk when mitigation steps start early enough. Just discussing risk with all the project flight elements during development, even if no risks are open, provides an excellent communication opportunity between systems engineering and those elements, ensuring concerns and worries have a platform for discussion. A well-managed risk identification process will identify concerns that are serious but not being clearly communicated, and it will enable mitigation of those potential problems before they cause a failure. Effective risk management requires considerable time and effort, but that effort will save time and money across the development. Risk management must be frequent enough to be useful and in depth enough to bring out emerging issues. It also requires a trusting relationship between the lead systems engineer and element and/or subsystem leads. The discussions need to be with the right number of individuals (typically a handful) and the right duration in time (typically an hour a month). Outside of these risk working groups, there is a formal management process to input, status, and disposition risks, and a monthly Risk Management Board meeting where key project stakeholders are informed. This paper provides good guidance on effective risk management from a systems engineering perspective and provides project lessons learned from the NASA spaceflight missions NICER, Landsat 9, LRO, and OSIRIS-REx to demonstrate the effectiveness of risk management.

Lessons Learned↗

NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

NASA NTRS2016

Analyzing Double Delays at Newark Liberty International Airport (EWR)

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular perceived inequity that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based scheduling of internal departures by the Traffic Management Advisor (TMA) (now operationally superseded by the FAA's the Time-Based Flow Management system). Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot easily fit into the arrival flow at the runway. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. TMA scheduling delays are found to be generally higher than TMA airborne metering delays, regardless of prior GDP delays. Depending on how the double delay is defined, between 42 and 62 of all internal departures in GDP and TMA scheduling experienced double delays in this period. A deep dive into the data reveals that contributors to double delays include upstream flights departing before their Expect Departure Clearance Times (EDCTs); differences in the rates used for setting EDCTs and TMA Scheduled Times of Arrival; differences in the arrival demand expected based on EDCTs and the arrival demand entering TMA; and shorter en route times between takeoff and entry into TMA than assumed in the calculation of flight EDCTs, all of which undermine the sequencing and spacing underlying flight EDCTs. Double delays are also found to coincide with periods in which the virtual runway arrival queue being served by a TMA is large, there are periods of high demand relative to capacity, and there are high airborne metering delays. Data mining techniques are used to confirm that each of these factors contribute to the occurrence of double delay andor high internal departure scheduling delay across three months of data from June to August 2010. Predictors of the occurrence of double delay and high TMA scheduling delay are built using logistic regression, providing prediction accuracies of 69 and 73, respectively.

traffic flow management↗

DOE OSTI2023

Measuring surface albedo for various crops

Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat

albedo↗

DOE OSTI2024

Albedo of crops as a nature-based climate solution to global warming

Abstract Surface albedo can affect the energy budget and subsequently cause localized warming or cooling of the climate. When we convert a substantial portion of lands to agriculture, land surface properties are consequently altered, including albedo. Through crop selection and management, one can increase crop albedo to obtain higher levels of localized cooling effects to mitigate global warming. Still, there is little understanding about how distinctive features of a cropping system may be responsible for elevated albedo and consequently for the cooling potential of cultivated lands. To address this pressing issue, we conducted seasonal measurements of surface reflectivity during five growing seasons on annual crops of corn-soybean–winter wheat ( Zea mays L.- Glycine max L. Merrill - Triticum aestivum L. ; CSW) rotations at three agronomic intensities, a monoculture of perennial switchgrass ( Panicum virgatum L. ), and perennial polycultures of early successional and restored prairie grasslands. We found that crop-species, agronomic intensity, seasonality, and plant phenology had significant effects on albedo. The mean±SD albedo was highest in perennial crops of switchgrass (0.179±0.04), intermediate in early successional crops (0.170±0.04), and lowest in a reduced input corn systems with cover crops (0.154±0.02). The strongest cooling potentials were found in soybean (-0.450 kg CO 2 e m -2 yr -1 ) and switchgrass (-0.367 kg CO 2 e m -2 yr -1 ), with up to -0.265 kg CO 2 e m -2 yr -1 of localized climate cooling annually provided by different agroecosystems. We also demonstrated how diverse ecosystems, leaf canopy, and agronomic practices can affect surface reflectivity and provide another potential nature-based solution for reducing global warming at localized scales.

Lei, Cheyenne (ORCID:0000000272746309)↗

NASA NTRSDate not supplied

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗

DOE OSTI2024

Mild chemical recycling of carbon fiber-reinforced epoxy composites in aqueous buffers and development of hydrothermally recyclable vitrimer composites from recyclates

Carbon fiber-reinforced polymer (CFRP) composites have gained widespread adoption across diverse industries. However, their inherent stability, stemming from the crosslinked structure of the matrix resin, poses a significant challenge in managing the growing volume of CFRP waste. Consequently, there is a pressing need for an eco-friendly upcycling method that effectively recovers and reuses both the valuable carbon fibers and the polymer matrix from CFRP waste. This study presents a novel approach for upcycling CFRP waste under environmentally friendly conditions. Firstly, CFRP waste with an amine-cured epoxy matrix was completely decomposed in aqueous buffer solutions under mild conditions (≤ 220 °C, pH = 4.8). Further, decomposed matrix polymer (DMP) was employed to transform conventional epoxy resins into recyclable vitrimers. Lastly, new composites that can be hydrothermally recycled were fabricated using both DMP and recovered carbon fibers. As a result, this work proposes a novel strategy for achieving a circular economy within the CFRP industry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

A Method for Evaluating and Tracking Production-Sample Test (PST) Delay Risk

This report describes a method for evaluating risk from delayed Production Sample Testing (PST), and strategies for reducing test backlogs. Risk contributions to overall risk from delayed PST include a Steady State Risk (SSR) contribution that is inherent in the qualified design and manufacturing processes, and a Non-Homogenous Production Risk (NHPR) contribution from production variation. Both definitions and evaluation techniques for these risk contributions are provided along with correlation to the standard Quality Assurance Process, QA001.2, risk ranking matrix. Methods for tracking test backlogs, and reducing backlogs are also discussed. The delayed PST evaluation method described here includes the merger of both slightly quantitative methods for tracking defect levels and the propensity for production variation with general risk management tracking tools like the likelihood vs. consequence risk ranking matrix. This merger is important because it allows more effective evaluation and communication with regards to delayed PST.

42 ENGINEERING↗

NASA NTRS2018

Recommendations Emerging from an Analysis of NASA's Deep Space Communications Capacity

During 2016-2017, NASA’s Space Communications and Navigation (SCaN) Office chartered a study of Deep Space Network (DSN) communications capacity relative to projected future-mission demand over the next 30 years. In this paper, we briefly describe the methodology used to analyze capacity vs. demand over such a broad timeframe, summarize key findings emerging from the analysis, and discuss the associated recommendations. Performing the analysis entailed: identifying key factors shaping the anticipated future mission set, identifying several alternative future mission set scenarios consistent with these factors, and then analyzing each mission set scenario in terms of required antenna capacity, downlink and uplink capabilities, and spectrum as a function of time. On the basis of these aggregate requirements, DSN loading simulations were then conducted that examined how well each of the postulated mission sets could load up onto the the DSN’s “in-plan” architecture. To the extent that capacity shortfalls emerged during these baseline simulations, architectural solutions to the shortfalls were then postulated and tested via additional simulations. In general, the trend analyses and baseline loading simulations indicated a significant progression in challenges over the next three decades. In the current decade, the DSN appeared to be operating very close to capacity. The first human exploration mission and its secondary payload launch opportunities for cubesats traveling beyond GEO contributed to this loading. As a consequence, the main challenge appeared to be managing peak assetcontention periods. In the next decade, the DSN continued to operate close to capacity but also began transitioning to more frequent human mission support. Upgrading for, and operating, a human-rated system while continuing to meet robotic mission customer requirements emerged as the key challenge. In the 2030’s and beyond, simulations suggested a need for fundamentally new capability and capacity. The high data rates and long link distances characteristic of human Mars exploration drove requirements far beyond what is currently “in plan.” The key challenge then became determining the most cost-effective combination of RF and optical assets for communicating with the postulated human Mars assets while still providing for the needs of all the other missions across the solar system. Various link budget, visibility, and loading analyses ultimately suggested that the human Mars exploration demands of the 2030’s could best be addressed with two cross-linked RF-optical areostationary relays (or an areostationary relay and deep space habitat) providing a dual “trunk link” to an array of 2-to-3 additional 34m beam waveguide antennas and an ~8.5m optical antenna at each DSN Complex. The dual “trunk link” would enable the same amount of total data return to Earth as a single trunk link at twice the data rate, but with only half the required array size on the ground, assuming use of Multiple Spacecraft Per Antenna (MSPA) techniques. MSPA techniques, including a Multiple Uplink Per Antenna (MUPA) technique currently under investigation, also showed promise for reducing asset contention in the decades prior to human Mars exploration.

Lee, Carlyn-Ann↗

NASA NTRS2022

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

NASA NTRSDate not supplied

Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗