Conceptual Phase Research Articles

Robust multidisciplinary analysis and optimization for conceptual design of flexible aircraft under dynamic aeroelastic constraints

We present a computational framework for robust multidisciplinary design and optimization of flexible aircraft, suited for the conceptual design exploration phase. Constraints are representative of some dynamic aeroelastic effects, including flutter and gust-induced structural stresses. Uncertainties on wing structural parameters are considered, and reliability-based optimization under dynamic aeroelastic constraints is addressed by a Bayesian approach. This work details the implementation aspects, covering disciplinary software tools and the overall aircraft design suite, the optimization algorithm and the approach to propagate uncertainty efficiently. Results are thoroughly discussed for a reference aircraft, which is optimized in the study with respect to a few wing parameters including aspect ratio. The proposed approach is compared to a conventional design methodology assuming a rigid airframe. We show that when applied to slender and flexible wings, the latter can produce dangerous non-conservative results, as its predictions are too optimistic both with respect to efficiency and to aeroelastic safety.

An Ontology-based Engineering system to support aircraft manufacturing system design

During the conceptual design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated against performance indicators in a collaborative engineering process. Domain experts’ knowledge and the motivations for decision-making is a crucial asset for enterprises which is challenging to be captured and capitalised. Ontology-based Engineering (OBE) systems emerge as a new generation of Knowledge-based Engineering techniques with advancements of ontology engineering methods and computer science technologies. Ontologies enable to capture both explicit and implicit domain knowledge from historical records and domain experts. These Ontology-based Engineering systems can stand highly complex collaborative design processes involving multidisciplinary stakeholders and various digital tools. This paper proposes a tradespace framework with Ontology-based Engineering features included on top of existing Model-Based System Engineering and interoperability capabilities. These additional Ontology-based Engineering features reuse formalised knowledge via knowledge graph technologies and generative algorithms, changing the cognitive process from the designer, to an automatic process which generates design alternatives for the designer. The tradespace framework is demonstrated in a case study to design the aircraft fuselage orbital joint process, helping the designer to take better strategic decisions at conceptual phase and proving to be an advantageous paradigm for the design process.

Scale decisions and good practices in socio-environmental systems modelling: guidance and documentation during problem scoping and model formulation

Models of socio-environmental or social-ecological systems (SES) commonly address problems requiring interdisciplinary scientific expertise and input from a heterogeneous group of stakeholders. In SES modelling multiple interactions occur on different scales among various phenomena. These scale phenomena include the technical, such as system variables, process detail, inputs and outputs, which most often require spatial, temporal, thematic and organisational choices. From a good practice and project efficiency perspective, the problem scoping and conceptual model formulation phase of modelling is the one to address well from the outset. During this phase, intense and substantive discussions should arise regarding appropriate scales at which to represent the different phenomena. Although the details of these discussions influence the path of model development, they are seldom documented and as a result often forgotten. We draw upon personal experience with existing protocols and communications in recent literature to propose preliminary guidelines for documenting these early discussions about the scale(s) of the studied phenomena. Our guidelines aim to aid modelling group members in building and capturing the richness of their rationale for scoping and scale decisions. The resulting transcripts are intended to promote transparency of modelling decisions and provide essential support for the justification of the final model for its intended use. They also facilitate adaptive modifications of the pathway of model development via retracing decisions and iterative reflection upon alternative scale options.

Predicting tunnel water inflow using a machine learning-based solution to improve tunnel construction safety

Water inflow is a typical and complicated geological hazard that may have a significant effect on both the building timeline and the safety of a tunnel under construction. Therefore, accurate water inflow estimation in tunneling is a key factor for the project's success. Such information is critical for the early conceptual and design phases, when key choices must be made. For this purpose, an optimized model based on the gene expression programming (GEP) method was proposed to estimate the water inflow in tunnels. An equation was generated for the optimized GEP model through the best fit of the predictions. Finally, by comparing the equation’s outputs with the actual ones and comparing its behavior with practice, its potential ability for estimating the water inflow of tunnels was approved. This model can reduce the uncertainties about tunnels and give machine learning development in tunnel planning.

Using Deep Reinforcement Learning for Assessing the Consequences of Cyber Mitigation Techniques on Industrial Control Systems

This paper discusses an in-progress study involving the use of deep reinforcement learning (DRL) to mitigate the effects of an advanced cyber-attack against industrial control systems (ICS). The research is a qualitative, exploratory study which emerged as a gap during the execution of two rapid prototyping studies. During these studies, cyber defensive procedures, known as “Mitigation, were characterized as actions taken to minimize the impact of ongoing advanced cyber-attacks against an ICS while enabling primary operations to continue. To execute Mitigation procedures, affected ICS components required rapid isolation and quarantining from “healthy” system segments. However today, with most attacks leveraging automation, mitigation also requires rapid decision-making capabilities operating at the speed of automation yet with human-like refinement. The authors settled on the choice of DRL as a viable solution to this problem due to the algorithm’s designs which involves “intelligent” decisions based upon continuous learning achieved through a rewards system. The primary theory of this study posits that processes informed by data sources relative to the execution path of an advanced cyber-attack as well as the consequences of deploying a particular Mitigation procedure evolve the system into an ever-improving defensive capability. This study seeks to produce a defensive DLR based software agent trained by a DRL based offensive software agent that generates policy refinements based upon extrapolations from a corrupted network state as reported by an IDS and baseline data. Results include an estimation rule that would quantify impacts of various mitigation actions while protecting the operational critical path and isolating an in-progress attack. This study is in a conceptual phase and development has not started.
 This research questions for this study are:
 RQ1: Can this software agent categorize correctly an in-progress cyber-attack and extrapolate the potential ICS assets affected?
 RQ2: Can this software agent categorize novel cyber-attacks and extrapolate a probable attack vector while enumerating affected assets?
 RQ3: Can this software agent characterize how operations are affected by quarantine actions?
 RQ4: Can this software agent generate a set of ranked recommended courses of action by effectiveness, and least negative effects on the operational critical path?

Creación y validación de un instrumento para cuantificar actitudes, conocimientos y dificultades en el abordaje de los problemas sociales

ObjectivesThe aim of the study was to develop and validate a questionnaire to assess attitudes, knowledge and difficulties in the management of social problems by paediatric care providers. MethodsThe development of the tool started with a conceptualization phase, followed by the design, pilot testing and psychometric evaluation of the questionnaire based on the responses obtained from 407 professionals. We performed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to assess the construct validity of the questionnaire. We used the normed fit index (NFI), the root mean square error of approximation (RMSEA), the χ2 test and the comparative fit index (CFI) to test the goodness of fit. We assessed reliability through the Cronbach's α coefficient of internal consistency. All quantitative analyses were performed with the Stata/SE software, version 16.1. ResultsThe EFA identified 12 factors. All factors exhibited a good internal consistency (Cronbach's α, .8434). The CFA showed the model was a good fit (RMSEA=.037). The NAI and CAI values were .742 and .797, respectively. ConclusionsThis questionnaire comprising 138 items distributed in 12 factors is a reliable and valid instrument to analyse the attitudes, knowledge and difficulties in the approach to social problems in children by paediatricians, which will allow the design of interventions according to the needs and deficiencies identified through it.

Extracting and Formalizing Criminal-law Terminology Using DEXTER

In this article we discuss the processes of terminology extraction and specialized knowledge conceptualization taking the field of criminal law as an illustrative case in point. Regarding the first process, we provide an overview of DEXTER, a tool that has proven effective in detecting specialized units from a collection of texts with minimal effort on the part of the user. Regarding the conceptualization phase, this article illustrates the conceptual definition of some representative units belonging to the field of "criminal offenders". The purpose of conceptual modeling along these lines is the inclusion of specialized units of thought into a knowledge base known as FunGramKB. The aim of this paper is to show that the combination of an extractor such as DEXTER with the semantic expressiveness of FunGramKB constitutes a solid basis for the improvement of specialized technological tools aimed at jurists, legal specialists, or other practitioners interested in legal terminology.

Cost and Material Quantities Prediction Models for the Construction of Underground Metro Stations

This paper addresses the gap in the scientific literature regarding construction cost estimates for the construction of underground metro stations. It provides preliminary cost estimation models using linear regression for use by the Greek underground metro public transport authority for planning future extensions to the Athens and Thessaloniki networks. At the same time, it contributes to the body of knowledge by proposing material quantity prediction models and presents a two-stage preliminary cost estimation model for the construction of civil engineering works of underground metro stations. Stage one uses the construction cost budgets of six metro stations in Greece to develop a multilinear regression equation for the prediction of the overall cost for construction of civil engineering works; stage two provides estimates of material quantities using linear regression, key quantity ratios, and artificial neural networks. The data analyzed are from the prior measurements of quantities for the construction of the Chaidari to Piraeus extension of the Athens Metro Line 3. After comparing the actual values of costs and quantities with the corresponding predictions, acceptable discrepancies are observed. All models provide estimates within ±25% discrepancies, which are acceptable at the conceptual planning phase in order to initiate project funding quests.

Image regression-based digital qualification for simulation-driven design processes, case study on curtain airbag

Today digital qualification tools are part of many design processes that make them dependent on long and expensive simulations, leading to limited ability in exploring design alternatives. Conventional surrogate modelling techniques depend on the parametric models and come short in addressing radical design changes. Existing data-driven models lack the ability in dealing with the geometrical complexities. Thus, to address the resulting long development lead time problem in the product development processes and to enable parameter-independent surrogate modelling, this paper proposes a method to use images as input for design evaluation. Using a case study on the curtain airbag design process, a database consisting of 60,000 configurations has been created and labelled using a method based on dynamic relaxation instead of finite element methods. The database is made available online for research benchmark purposes. A convolutional neural network with multiple layers is employed to map the input images to the simulation output. It was concluded that the showcased data-driven method could reduce digital testing and qualification time significantly and contribute to real-time analysis in product development. Designers can utilise images of geometrical information to build real-time prediction models with acceptable accuracy in the early conceptual phases for design space exploration purposes.

Architecting the Metaverse: Blockchain and the Financial and Legal Regulatory Challenges of Virtual Real Estate

There has been disagreement over the value of purchasing space in the metaverse, but many businesses including Nike, The Wendy’s Company, and McDonald’s have jumped in headfirst. While the metaverse land rush has been called an “illusion” given underdeveloped infrastructure, including inadequate software and servers, and the potential opportunities for economic and legal abuse, the “real estate of the future” shows no signs of slowing. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the long-term legal and regulatory considerations of capitalizing on the investment, as well as the manner in which blockchain technology can secure users’ data and digital assets, has yet to be properly investigated. With the metaverse still in a conceptual phase, building a new 3D social environment capable of digital transactions will represent most of the initial investment in time in human capital. Digital twin technologies, already well-established in industry, will be ported to support the need to architect and furnish the new digital world. The return on and viability of investing in the “real estate of the future” raises questions fundamental to the success or failure of the enterprise. As such this paper proposes a novel framing of the issue and looks at the intersection where finance, technology, and law are converging to prevent another Dot-com bubble of the late 1990s in metaverse-based virtual real estate transactions. Furthermore, the paper will argue that these domains are technologically feasible, but the main challenges for commercial users remain in the legal and regulatory arenas. As has been the case with the emergence of online commerce, a legal assessment of the metaverse indicates that courts will look to traditional and established legal principles when addressing issues until the enactment of federal and/or state statutes and accompanying regulations. Lastly, whereas traditional regulation of real estate would involve property law, the current legal framing of ownership of metaverse assets is governed by contract law.

An approach to the selection of design parameters based on conflict with constraints

The Axiomatic Design (AD) supports decision-making based on the axioms of independence and information. In the engineering design activity, the designer must make early decisions that impact the success of the project. These decisions are of paramount importance in the design of one-off products. In these products, one must make decisions in the early design phases, with scarce data about the product that will undeniably affect the solution. Applying the information axiom requires data from the alternative solutions under consideration that for one-off products are most often non-existent in the conceptual phase of the design.Additionally, the design process is highly conditioned by existing constraints, which significantly influence the outcome. This work suggests selecting design parameters (DP) for one-off products from different sets of proposals that comply with the independence of functional requirements (FR). AD design follows a hierarchical decomposition process from a conceptual to a detailed design. The proposed method allows selecting the DPs among the set of alternatives by quantifying the degree of conflict each solution presents to the constraints. It shows the first step to define the DPs, at each level of decomposition of the AD process. It is the first step to establish a zig in AD or, otherwise, a way to find a solution in the conceptual phase. It applies to one-off products – any product with one chance to be right. The paper applies this method to the DP selection of a manipulation device.

The Coming of Age of Space Satellite Industry: Transitioning from a Growth to a Maturity Life Cycle Phase

From the perspective of the evolution of modern mass-production industrial sectors, the establishment of an industry can occur in a typical sequence of four conceptual phases: the introduction phase, in which a new technological concept is introduced; the growth phase, in which application of this concept in the form of a product or service is undertaken; the maturity phase, in which the direct use of the product and the advent of product-enabled services establish the new economic sector, and an eventual decline phase when one or more substitute products appear. Most of the current industrial products may be considered systems. The application of established concepts, such as interchangeable parts, permits firms to manufacture systems on a large scale, making sophisticated products available to society at manageable prices. The large availability of a product in a socioeconomic environment favors the use of this product in innovative ways, many of them unprecedented. In this way, introducing an innovative product in the market may nucleate a whole new industry over time, which may experience growth either through the continual evolvement of the product or expansion of the breadth of applications. Recent years have shown impressive development in the space industry. This article presents data that suggests that the global satellite space industry is transitioning from a growth to a maturity stage. It will be argued that barriers to entry are still at a level that permits Brazil, given its current position, to engage in the global space industry.

Lightweight creativity methods for idea generation and evaluation in the conceptual phase of lightweight and sustainable design

Regarding the implementation of lightweight design in products, there are various guidelines, principles and methods that support the developers methodically throughout the entire design process. Such methods often pursue the goal of optimizing an existing product by reducing the amount of consumed material (e.g., topology optimization). A more effective way to apply lightweight design lies in fostering the creativity and intuitiveness of engineers to develop miscellaneous concepts with the capability to provide far greater mass reductions in contrast to smaller efficiency enhancements. Supported through the breakdown of assemblies via thinking in terms of functions along the paradigm of systems engineering, existing creativity techniques (e.g., “brainstorming” or “6-hats-method”) and evaluation methods (e.g., “point scoring”) for idea generation and evaluation have been analyzed and rethought from a lightweight and sustainable design perspective resulting in so called lightweight creativity methods (LWCM). The methods were tested on a use case from the field of robotics, which enabled the identification of the potential of LWCM for a lightweight and sustainable design.

CONCEPTUALIZATION OF MODULAR PRODUCTS FOR THE PROSUMER. A DESIGN WORKSHOP

Modular design has proven to bring numerous advantages in the design and development of new products, but its relationship with the end user has been limited in practical scope. Previous studies analyze its applicability for prosumer users, but it has not yet been tested as a design method. This work presents a first application in a design workshop carried out during the conceptualization phase of a real project. The objective was to design a multifunction portable cart that complies with the characteristics of modular design and is focused on prosumers. This conceptualization was developed by designers and prosumers with the purpose of designing modular products for the prosumer. To do this, the key terms and the design method were explained to the participants. Subsequently, two group exercises were carried out to devise new applications and propose limitations and solutions. The workshop concludes with the individual conceptualization of the product, giving rise to 22 design concepts that were evaluated by the participants. Due to the lack of consensus, a second evaluation was carried out by the three coordinators of the workshop. The highest rated concept was fully evolved and developed, including manufacturing. The results offer conclusions on how the participants applied the method, what were the most applied characteristics of modular design, what manufacturing tools were proposed for prosumers and how to approach the method to non-specialized users. Keywords: design method, prosumer, modular design, workshop, conceptualization

Theoretical Aspects of Social Enterprises

Social enterprises are given special attention from a scientific and public policy point of view. In everyday life, we see them as organizations that can provide solutions to various social problems. From an academic perspective, they represent a new research topic with its own interdisciplinary nature. They have been examined mainly from the point of view of management and organizational culture. In terms of scientific analysis, the newly developed research area of social economy and social enterprises is still in the conceptualization phase. The theoretical and methodological framework for research measurements need to be finalized. In this study, we seek to answer the question of how social economy—in particular, the perception of social enterprises in international and Romanian literature—is changing as a result of economic and social changes in space and time. We examine the factors along which definitions of the social enterprise within social economy are attempted, and the indicators that facilitate the investigation of the social impact of social enterprises.

Ecological and Confined Domain Ontology Construction Scheme Using Concept Clustering for Knowledge Management

Knowledge management in a structured system is a complicated task that requires common, standardized methods that are acceptable to all actors in a system. Ontology, in this regard, is a primary element and plays a central role in knowledge management, interoperability between various departments, and better decision making. The ontology construction for structured systems comprises logical and structural complications. Researchers have already proposed a variety of domain ontology construction schemes. However, these schemes do not involve some important phases of ontology construction that make ontologies more collaborative. Furthermore, these schemes do not provide details of the activities and methods involved in the construction of an ontology, which may cause difficulty in implementing the ontology. The major objectives of this research were to provide a comparison between some existing ontology construction schemes and to propose an enhanced ecological and confined domain ontology construction (EC-DOC) scheme for structured knowledge management. The proposed scheme introduces five important phases to construct an ontology, with a major focus on the conceptualizing and clustering of domain concepts. In the conceptualization phase, a glossary of domain-related concepts and their properties is maintained, and a Fuzzy C-Mean soft clustering mechanism is used to form the clusters of these concepts. In addition, the localization of concepts is instantly performed after the conceptualization phase, and a translation file of localized concepts is created. The EC-DOC scheme can provide accurate concepts regarding the terms for a specific domain, and these concepts can be made available in a preferred local language.

Equitable implementation of innovations to promote successful aging in place.

Equitable implementation of innovations to promote successful aging in place.

Transformation of Architectural Design Concepts During the Early Design Phase

The most difficult objective for students in an architectural design studio during the early design phase is to produce a design concept satisfyingly. This is due not just to the difficulty of selecting an appropriate method of approaching concepts, but also because of the many transformations associated with the concept's evolution over time.
 This research examines the modifications that occur throughout the conceptual phase of a design session, which typically lasts a few weeks. We hypothesize that while students' conception methods have been more abstract in creating a concept, they are subject to more alterations during the early phase of design. The research conducts concept generation and transformations by monitoring a group of fourth-grade architecture students through their design process. It also tries to link those transformations to the various methods utilized by students to create their concepts. It appears that the transformations that occurred throughout the design sessions were either formal or functional-oriented. Observations clarify that those transformations are linked to the sort of concept generating, which is either abstract or concrete. By observing the design sessions, the research was able to confirm the previous hypothesis. The modifications implemented to the design concepts were obviously tied to the nature of their selection of methods of production. When compared to concrete nature concepts, abstract nature concepts were more vulnerable to transformations throughout the conceptual phase of the design task on the scope of form and function.

Schema therapy for patients with borderline personality disorder and comorbid alcohol dependence: A multiple-baseline case series design study.

This study tested the effectiveness of schema therapy (ST) for borderline personality disorder (BPD) and comorbid alcohol dependence (AD). Twenty patients participated in a case series study with multiple baselines. The baseline phase consisted of treatment as usual. It was followed by a case conceptualization phase, an experiential techniques phase and a behavioural change phase. Patients showed a significant decrease in BPD and AD symptoms; change was mainly accomplished in the experiential techniques phase, with medium to large effect sizes. Three months after termination of therapy, 68% of the patients had remitted from BPD, and the number of drinking days decreased clearly. This study shows that, although treatment is challenging in this group of patients, meaningful change can be obtained in patients with BPD and AD using ST.

Assessment of Orofacial Symptoms in Juvenile Idiopathic Arthritis: Validation of a Consensus-Based Short Patient Questionnaire.

To develop, validate, and test the performance of patient-reported outcomes (PROs) in a short patient questionnaire (< 5 minutes in length) in order to assess the multidimensional aspects of orofacial symptoms related to juvenile idiopathic arthritis (JIA) among patients aged ≥ 10 years. The study was conducted by an interdisciplinary task force from the Temporomandibular Joint Juvenile Arthritis Working Group. The project consisted of a multiphased approach including the following: (1) conceptual phase with online international survey of 167 healthcare workers, (2) item generation and drafting of preliminary questionnaire(s) (ie, face validity), (3) cognitive script interview and probing (ie, content validity; 16 patients with JIA), (4) assessment of construct validity (ie, convergence and divergence; 53 patients with JIA), (5) test of reliability, and (6) test of clinical performance and psychometric characteristics (95 patients with JIA). In total, 7 PROs were included in the final patient questionnaire: (1) pain frequency, (2) pain intensity, (3) pain location, (4) jaw function, (5) specific questions related to symptoms and dysfunction, (6) changes in face and jaw pain since last visit, and (7) changes in jaw function since last visit. In total, 80% of the patients were able to complete the questionnaire in less than 5 minutes. We have developed and validated a short patient questionnaire to assess the multidimensional aspects of JIA-related orofacial symptoms. The PROs included in our questionnaire show acceptable validity and reliability. The questionnaire is applicable to routine monitoring of subjects with JIA, as well as future research studies.