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The paper aims to provide methodological support for hybrid project management, in which the discipline of predictive methodologies combines with the flexibility of adaptive ones. Specifically, the paper explores the extent complexity and volatility dimensions of organisational problems inform choices of PM methodologies both theoretically and in current practice, as a first step towards better methodological support for hybridisation.

The paper takes a mixed method approach, including both secondary research and primary research with practitioners. Primary research consists of a small scale survey (n = 31) followed by semi-structured interviews, with findings triangulated against secondary evidence.

The paper provides empirical insights on how complexity and volatility of organisational problems can inform hybrid project management practices. Specifically, it suggests a mapping between volatility and complexity dimensions and predictive and adaptive risk controls as a first step towards the systematisation of hybrid combinations in projects.

Due to the small participant sample, the research results may lack generalisability.

The paper includes implications for the development of methodological support for setting up hybrid projects in practice.

The paper addresses a gap acknowledged both in the literature and by practitioners.

This paper aims to propose a global adaptive direct slicing technique of Non-Uniform Rational B-Spline (NURBS)-based sculptured surface for rapid prototyping where the NURBS representation is directly extracted from the computer-aided design (CAD) model. The imported NURBS surface is directly sliced to avoid inaccuracies due to tessellation methods used in common practice. The major objective is to globally optimize texture error function based on the available range of layer thicknesses of the utilized rapid prototyping machine. The total texture error is computed with the defined error function to verify slicing efficiency of this global adaptive slicing algorithm and to find the optimum number of slices. A variety of experiments are conducted to study the accuracy of the developed procedure, and the results are compared with previously developed algorithms.

This paper proposes a new adaptive algorithm which globally optimizes a texture error function produced by staircase effect for a user-defined number of layers. The adaptive slicing algorithm dynamically calculates optimized slicing thicknesses based on the rapid prototyping machine’s specifications to minimize the texture error function. This paper also compares the results of implementing the developed methodology with the results of previously developed algorithms and presents cost-effective optimum slicing layer thicknesses.

A new methodology for global adaptive direct slicing algorithm of CAD models, based on a texture error function for the final product and the possible layer thicknesses in rapid prototyping, has been developed and implemented. Comparing the results of implementation with the common practice for several case studies shows that the proposed approach has greater slicing efficiency. Typically, by utilizing this approach, the number of prototyping layers can be reduced by 20-50 per cent compared to the slicing with other algorithms, while maintaining or improving the accuracy of the final manufactured surfaces. Therefore, the developed slicing method provides a better solution to trade-off between the rapid prototyping time and the rapid prototyping accuracy. For the many advantages of global direct slicing, it can be seen as the future solution to the slicing process in rapid prototyping systems.

This paper presents an innovative approach in direct global adaptive slicing of the additive manufacturing parts. The novel definition of an error function which comprehensively addresses the resulting manufactured surface quality of the entire product allows presenting an objective function to solve and to find the optimum selection of all the layer thicknesses during the slicing process.

This paper aims to present an adaptive approach of the generalized finite element method (GFEM) for transient dynamic analysis of bars and trusses. The adaptive GFEM, previously proposed for free vibration analysis, is used with the modal superposition method to obtain precise time-history responses.

The adaptive GFEM is applied to the transient analysis of bars and trusses. To increase the precision of the results and computational efficiency, the modal matrix is responsible for the decoupling of the dynamic equilibrium equations in the modal superposition method, which is used with only the presence of the problem’s most preponderant modes of vibration. These modes of vibration are identified by a proposed coefficient capable of indicating the influence of each mode on the transient response.

The proposed approach leads to more accurate results of displacement, velocity and acceleration when compared to the traditional finite element method.

In this paper, the application of the adaptive GFEM to the transient analysis of bars and trusses is presented for the first time. A methodology of identification of the preponderant modes to be retained in the modal matrix is proposed to improve the quality of the solution. The examples showed that the method has a strong potential to solve dynamic analysis problems, as the approach had already proved to be efficient in the modal analysis of different framed structures. A simple way to perform h-refinement of truss elements to obtain reference solutions for dynamic problems is also proposed.

This paper aims to propose an adaptive unstructured finite volume procedure for efficient prediction of propellant feedline dynamics in fluid network.

The adaptive strategy is based on feedback control of errors defined by changes in key variables in two subsequent time steps.

As an evaluation of the proposed approach, two feedline dynamics problems are formulated and solved. First problem involves prediction of pressure surges in a pipeline that has entrapped air and the second is a conjugate heat transfer problem involving prediction of chill down of cryogenic transfer line. Numerical predictions with the adaptive strategy are compared with available experimental data and are found to be in good agreement. The adaptive strategy is found to be efficient and robust for predicting feedline dynamics in flow network at reduced CPU time.

This study uses an adaptive reduced-order network modeling approach for fluid network.

This study aims to examine the rehabilitation project of the iconic urban industrial building in Athens, “FIX” brewery, and the practices followed, so as to initiate a discussion on the role of the façades in such a process. In particular, this study suggests that by choosing to restore just two of the façades out of the whole building, while placing emphasis on creating a new face for the new use, frontality is promoted against the pre-existing homogeneity approach, and façadism is introduced. However, both façadism and frontality distance this project from the rationale behind the adaptive reuse and redevelopment of built heritage.

A thorough architectural analysis of the FIX brewery building's long history and its consecutive transformations, besides providing adequate evidence for the hypothesis set, provided the opportunity to broaden the scope of this research and explore the role of the façades in adaptive reuse practice. Methodology-wise, this research was further strengthened by a comparative analysis of the Weverij De Ploeg adaptive reuse project in Bergeijk.

In the light of this critical analysis, the current study first highlights the importance of a building's façades in shaping public perception and establishing a connection to the city, by transmitting information and meanings about the building's structure, function, character and era. Accordingly, it stretches the need for façades' retention when adapting an industrial building of cultural heritage to a new use. Second, it emphasizes the need of fostering a holistic perspective toward a historic industrial building of such merit, respecting the building as a whole and in all its depth.

This in-depth analysis provides a solid ground for rethinking adaptive reuse, concretizing the appropriate approaches to industrial buildings of cultural heritage from parties involved (inter alia government leaders, legislators, property developers, historians, urban planners, architects and other engineers), to ensure both the building's continuity and longevity, and an efficient and sustainable urban regeneration.

The purpose of the proposed research methodology is to control the trajectory tracking of EDRM and also to cancel out the effect of no-smooth nonlinearities, which affect the system performance badly.

Robust adaptive neural network (RANN)-based backstepping control design methodology is presented in this paper. The proposed design methodology improves the trajectory tracking and running mean error.

The running mean error results show that the convergence of the proposed RANN-based backstepping technique is very fast as compare to the conventional PD control and due to this proposed control technique, the EDRM follows its desired trajectory perfectly.

The EDRM trajectory tracking performance increases which leads to a better working position of EDRM.

The originality of this research article is 93 per cent.

Gives a bibliographical review of the error estimates and adaptive finite element methods from the theoretical as well as the application point of view. The bibliography at the end contains 2,177 references to papers, conference proceedings and theses/dissertations dealing with the subjects that were published in 1990‐2000.

This paper aims to present a generic lifecycle framework model for guiding architects, engineers, contractors and facilities managers (AEC/FM) practitioners on the effective implementation of adaptive reuse projects.

A mixed approach of qualitative and quantitative techniques was followed in the development of the framework model. A literature review was conducted to comprehend the processes involved in adaptive reuse projects. In total, 90 AEC/FM practitioners were surveyed to identify the current practices in these projects. A generic framework model was then developed to standardize the processes involved, using integration definition for function modeling process modeling methodology. Face-to-face interviews with a targeted group of 30 AEC/FM practitioners were conducted, to validate the developed framework model, by assessing the importance and the frequency of implementing each function in the developed framework model.

The framework model consisted of four sequential processes, namely, assess the feasibility of the adaptive reuse project, design the adaptive reuse project, construct the adaptive reuse project and operate and maintain the adaptive reuse project. The validation confirmed the importance of all the framework functions and the frequency of their implementation.

This research contributes to the literature and the AEC/FM professions, through developing a lifecycle and knowledge-oriented framework model for building adaptive reuse. The framework presents clear documentation of adaptive reuse processes. Thus, it holds the potential of endeavoring on adaptive reuse projects to be more efficient.

The purpose of this paper is to explore the feasibility of developing an adaptive strategy to address the impact of climate change in the context of flooding.

The paper analyses flood risk and highlights the need for an adaptive strategic plan for flood risk management under the impact of climate change. It introduces a framework for the development of an adaptive strategic plan. The paper identifies organizational issues (at the local government scale) associated with having an adaptive strategic plan and developing a methodology to address these issues. It also identifies the need for a strategic decision support system (SDSS) and conceptualizing the system in order to support adaptive planning principle.

This study identifies lack of adaptability as a gap in traditional strategic planning for addressing flood risk associated with climate change. An adaptive strategic plan has adequate flexibility, promptness and responsiveness to adapt itself to new realities as they emerge and can sustain itself and remain relevant in a changing environment. The study introduces a SDSS that is necessary to support the adaptive element of an adaptive strategic plan.

This study distinguishes between a strategy for adaptation and an adaptive strategy. Most research on the topic of adaptation to climate change have been focused on developing strategies that offer adaptive solutions to pressing problems such as flooding. For instance, they may recommend more investment on non‐structural methods for flood mitigation, as they are more adaptive than alternative structural methods and therefore more sustainable under climate change. An issue that has attracted less attention is the fact that the strategic plans themselves (or in a sense the decision‐making framework) need to be equally adaptive. Some of public institutions do not have adequate flexibility and promptness to change and rectify high‐level strategic plans. The study identifies the lack of an SDSS, which allows new scientific findings to be converted to new policies in a short period of time, as a reason for absence of promptness, responsiveness and flexibility in such organizations. This study makes an attempt to address this issue by suggesting a frame work that will enable a government institution to become more responsive to change.

The purpose of this paper is to build a bridge between climate change adaptation and spatial planning and design. It aims to develop a spatial planning framework in which the properties of climate adaptation and spatial planning are unified.

Adaptive and dynamical approaches in spatial planning literature are studied and climate adaptation properties are defined in a way they can be used in a spatial planning framework. The climate adaptation properties and spatial planning features are aggregated in coherent groups and used to construct the spatial planning framework, which subsequently has been tested to design a climate adaptive region.

The paper concludes that the majority of spatial planning methods do not include adaptive or dynamic strategies derived from complex adaptive systems theory, such as adaptive capacity or vulnerability. If these complex adaptive systems properties are spatially defined and aggregated in a coherent set of spatial groups, they can form a spatial planning framework for climate adaptation. Each of these groups has a specific time dimension and can be linked to a specific spatial planning “layer”. The set of (five) layers form the spatial planning framework, which can be used as a methodology to design a climate adaptive region.

Previous research did not connect the complex issue of climate change with spatial planning. Many frameworks are developed in climate change research but are generally not aiming to meet the needs of spatial planning. This article forms the first attempt to develop a spatial planning framework, in which non‐linear and dynamical processes, such as climate adaptation, is included.