Integrated Design Problem Research Articles

Humanitarian transportation network design via two-stage distributionally robust optimization

Natural disasters are highly unpredictable, with varying degrees of magnitude, and thus require a reliable and robust humanitarian relief network. Faced with the adverse effects of disasters, we advocate taking pre-disaster preventive actions, e.g., road link strengthening, to mitigate post-disaster disruptions to road networks. In this paper, we study a highly integrated humanitarian relief network design problem, in which the network strengthening plan and inventory pre-positioning scheme are optimized cooperatively. The proposed problem is formulated as a two-stage distributionally robust optimization (DRO) model, in which the first and second stages correspond to pre- and post-disaster relief operations, respectively. By leveraging prior data and the Wasserstein metric, a tailored ambiguity set is constructed to capture both node- and link-wise uncertainties. We demonstrate that the two-stage DRO model over the Wasserstein ambiguity set has an equivalent reformulation that can be solved via the L-shaped method with bilinear subproblems. Based on observations of the problem structure and the spirit of separation optimization, both exact and heuristic approaches are proposed to address the bilinear subproblems. Via the case study of the Yushu earthquake, we highlight the value of jointly optimizing network strengthening and inventory pre-positioning decisions. Specifically, with the same investment budget, integrating network strengthening into inventory pre-positioning can easily achieve an approximately 60% reduction in shortage penalties. Furthermore, our method can produce reliable solutions, based on which we explore several managerial implications.

Integrated optimization in operations control and systems design for carbon emission reduction in building electrification with distributed energy resources

Building electrification with distributed energy resources (DERs) is a promising strategy to decarbonize the building sector. Considering the inter-dependencies between operations control and systems design, integrating technology operations control optimization with DERs investment optimization can cost-effectively enhance such building decarbonization opportunities. This study proposes a multi-timescale integrated optimization framework to simultaneously optimize the design and control of DERs and electrification technologies for buildings. A novel building operational performance prediction model based on deep learning is developed to approximate and replace the computationally expensive control optimization. This helps resolve the challenging, computationally intractable multi-timescale integrated design and control optimization problem. Applying the proposed framework to a residential building, our results demonstrate its effectiveness in cost-efficient carbon emissions reduction. With integrated design and control optimization for DERs and electric building energy systems, the proposed framework reduces operational carbon emissions by 80% and total costs by 2.7% compared to a base case, which uses typical conventional building energy systems without DERs and control/design optimization. Separate optimization of operations control and system design cannot achieve such performance. Further scenario analyses indicate that as power grids become cleaner, the reliance on DERs can be alleviated but remain important in building carbon emission reduction under 2050 power grid scenario. Overall, as our results demonstrate, it is possible to reduce building operational carbon emissions simultaneously with net electrical load: compared to the base case, the proposed framework helps reduce the carbon emission by 80% while driving down the net electrical load from 44.1 to 19.3 kWh/m2/year.

Key Technology of Intelligentized Welding Manufacturing and Systems Based on the Internet of Things and Multi-Agent

With the development of the Internet of Things (IoT), Big Data, Artificial Intelligence technology, and the emergence of modern information technologies such as intelligent manufacturing, welding systems are changing, and intelligentized welding manufacturing and systems (IWMS) utilizing these technologies are attracting attention from both academia and industry. This paper investigates sensing technology, multi-information sensor fusion technology, feature recognition technology, the quality prediction method, control method, and intelligent welding production line application in the IWMS. Combining IoT technology and multi-agent systems, a hierarchical structure model welding manufacturing system (IoT-MAS) in the form of “leader-following” was constructed. The multi-agent welding manufacturing system has the advantages of distribution, intelligence, internal coordination and so on. The IoT-MAS consists of several sub-agents, which are divided into five categories according to their functions and internal processing logic. Combined with the functions of the intelligent welding manufacturing system, the agent structure of the whole welding process was proposed, and the matching communication technology and algorithm were designed. The intelligent welding manufacturing system based on IoT-MAS proposed in this paper can effectively solve the integrated design problem of large welding manufacturing systems.

Noise distribution law of air-conditioning ducts for metro vehicles

The passenger comforts are directly affected by the air supply uniformity and noise of air-conditioning duct inside the metro vehicle. In order to solve the integrated design problem of air supply uniformity and noise control of air-conditioning ducts, a theoretical model is established to analyze the air supply uniformity, noise attenuation, and airflow regeneration noise of the air-conditioning duct. The distribution law of the sound pressure level along the longitudinal air outlet was calculated, and the calculated results were compared with test ones. For a typical air supply duct with a constant cross section: (1) In order to ensure air supply uniformity at the outlet of the static pressure chamber, the area of the side air hole should be gradually increased in an exponential form along the direction of the main flow, and cannot be designed in the equal area form. (2) The airflow speed of each side hole decreased in sequence along the air duct length. In order to ensure the uniformity air supply of each side hole, the area of each side hole must be gradually increased. (3) The noise in the air conditioner duct was mainly concentrated at the front end of the air duct, and the noise at the subsequent air outlet can fully meet the current requirements of subway vehicles for indoor noise. Therefore, the front end of the air duct is the most important area for noise control.

Смешанный формат обучения – перспективное направление подготовки студентов экономических специальностей

Unpredictable abrupt changes in the external environment of the education ecosystem have necessitated the introduction of distance and mixed learning formats into practice and the transformation of forms of interaction between students and teachers. The high quality of students' training in higher education institutions has recently been ensured thanks to the implementation of online courses and the organization of mixed forms of education based on them, which involve remote work to familiarize students with theoretical material by performing skill-oriented tasks remotely, face-to-face seminars and final control of the development of academic disciplines. The subject of the article is a methodological approach to the organization of learning processes taking into account the challenges of the external environment and internal restructuring based on the integration of modern pedagogical teaching methods and technological solutions in order to form a new generation of human capital. The purpose of the work is to substantiate the construction of an integrated design—problem approach in conditions of mixed learning using LMS Canvas as a tool to improve the quality of training of a new generation of human capital. The conceptual foundations of designing the implementation of students' research work in a mixed learning format as an element of professional training of human capital are considered. The conclusions are made that the active inclusion of students in the modern process of the knowledge economy brings them to a high level of responsibility and strict compliance with deadlines for individual stages of work.

Integrated ionic liquid and rate‐based absorption process design for gas separation: Global optimization using hybrid models

AbstractA new method for integrated ionic liquid (IL) and absorption process design is proposed where a rigorous rate‐based process model is used to incorporate absorption thermodynamics and kinetics. Different types of models including group contribution models and thermodynamic models are employed to predict the process‐relevant physical, kinetic, and thermodynamic (gas solubility) properties of ILs. Combining the property models with process models, the integrated IL and process design problem is formulated as an MINLP optimization problem. Unfortunately, due to the model complexity, the problem is prone to convergence failure. To lower the computational difficulty, tractable surrogate models are used to replace the complex thermodynamic models while maintaining the prediction accuracy. This provides an opportunity to find the global optimum for the integrated design problem. A pre‐combustion carbon capture case study is provided to demonstrate the applicability of the method. The obtained global optimum saves 14.8% cost compared with the Selexol process.

Integrated design of unmanned aerial mobility network: A data-driven risk-averse approach

In this paper, we propose an integrated design problem of Unmanned Aerial Mobility Network (UAMN), which includes airport location selection (strategic decision) and routes planning (operational decision) to minimize the total cost, while guaranteeing flow constraints, capacity constraints, and electricity constraints. To facility expensive long-term infrastructure planning facing demand uncertainty, we develop a data-driven risk-averse two-stage stochastic optimization model based on the Wasserstein distance. The analysis of the numerical examples proves that our DRO framework provides a relatively robust solution for UAMN. Also, we find that the optimal network configuration is affected by the “pooling effects”, which is proved by the fact that the total infrastructure costs can be saved by pooling drone flows into a small number of high-capacity channels/transfer airports. Interestingly, a candidate node without historical demand records can be chosen to locate an airport, in case the demand surges up at this node. We demonstrate the application of our model for a real medical resources transportation problem with our industry partner, collecting donated blood to a blood bank in Hangzhou, China.

Process Systems Engineering Perspective on the Design of Materials and Molecules

This paper aims to provide an overview of the current state of the art in molecule and material design and a perspective on open questions. First, we discuss the interplay between process design and the design of molecules and materials and then present the basic trade-offs and interdependencies that need to be considered in this integrated design problem. Second, we introduce methods and open questions in the area of processing materials, with special emphasis placed on heterogeneous catalysts due to their importance in the chemical industry. Finally, we discuss materials for photovoltaic cells as one example of a chemical product that is likely to help supply sustainable energy and address climate change concerns. What is presented here is based on presentations and discussions during the FIPSE-4 meeting in June 2018 (https://www.fi-in-pse.org/fipse-4-2018).

Knowledge-Based Design Guidance System for Cloud-Based Decision Support in the Design of Complex Engineered Systems

AbstractThe automation and intelligence highlighted in Industry 4.0 put forward higher requirements for reasonable trade-offs between humans and machines for decision-making governance. However, in the context of Industry 4.0, the vision of decision support for design engineering is still unclear. Additionally, the corresponding methods and system architectures are lacking to support the realization of value-chain-centric complex engineered systems design lifecycles. Hence, we identify decision support demands for complex engineered systems designs in the Industry 4.0 era, representing the integrated design problems at various stages of the product value chain. As a response, in this paper, the architecture of a Knowledge-Based Design Guidance System (KBDGS) for cloud-based decision support (CBDS) is presented that highlights the integrated management of complexity, uncertainty, and knowledge in designing decision workflows, as well as systematic design guidance to find satisfying solutions with the iterative process “formulation-refinement-exploration-improvement” (FREI). The KBDGS facilitates diverse multi-stakeholder collaborative decisions in end-to-end cloud services. Finally, two design case studies are conducted to illustrate the proposed work and the efficacy of the developed KBDGS. The contribution of this paper is to provide design guidance to facilitate knowledge discovery, capturing, and reuse in the context of decision-centric digital design, thus improving the efficiency and effectiveness of decision-making, as well as the evolution of decision support in the field of design engineering for the age of Industry 4.0 innovation paradigm.

Distributionally robust fault detection design and assessment for dynamical systems

We present a novel distributionally robust optimization approach for integrated design and assessment of fault detection system. Its salient feature is the guaranteed robustness against the inexactness of probability distribution of unknown disturbances. The integrated design problem is formulated as a distributionally robust chance constrained program (DRCCP). It maximizes fault detectability subject to the constraint on the worst-case false alarm rate among a continuum of probability distributions. The moment-based and Wasserstein ambiguity sets are used as two different ways of uncertainty description, which differ manifestly from generic settings where disturbances follow either Gaussian or norm-bounded assumptions. We show that the use of two different ambiguity sets in fault detection leads to specific statistical properties. To solve DRCCPs efficiently, we develop exact reformulations and tailored solution algorithms, and in some cases the optimal solution turns out to be classical fault detection design. In addition, a distributionally robust assessment strategy is developed, which evaluates the worst-case and best-case detectability under known faults by solving tractable convex programs. The efficacy of the proposed approach is illustrated on the fault detection of a laboratory three-tank system.

Integrated Design of Fault Estimation and Fault-Tolerant Control for Closed-Loop Systems With Uncertain Short Delay

In this paper, an integrated design scheme of fault estimation (FE) and fault-tolerant control (FTC) is presented for a closed-loop system with uncertain short delay. Firstly, a closed-loop system with uncertain short delay is modeled as a system with uncertain parameters, and a bi-directional robustness interaction of uncertainty between the observer and the control system is analyzed. Then a fault estimation observer and a fault-tolerant controller are constructed, and the integrated design problem is converted into a robust control problem for the augmented system under $H_{\infty }$ performance index. Furthermore, the parameters of the fault estimation observer and fault-tolerant controller are solved by Lyapunov function and relaxation methods. Finally, the effectiveness and superiority of the proposed method are verified by an aircraft simulation.

Integrated design of topology and material for composite morphing trailing edge based compliant mechanism

The morphing trailing edge based compliant mechanism is a developing technology which can increase lift-drag ratio for variable flight modes by bending down the trailing edge. Composite material design is integrated into topology optimization for the morphing trailing edge based compliant mechanism in the paper. A two-step optimization strategy is established to solve the integrated design problem. Initially, lamination parameters are introduced and viewed as a bridge between structure stiffness and fiber angles for composite material. Design variables include the lamination parameters and element density. The least-squares between actual and desired displacements at output points along trailing edge is adopted to evaluate the deformed capability of the trailing edge. An integrated optimization model for the composite morphing trailing edge is established with the volume constraints. The optimal topologic shape and lamination parameters are initially obtained. Subsequently, a least-squares optimization between fiber angles and the optimal lamination parameters is implemented to obtain optimal fiber angles. Finally, morphing capability of composites trailing edge based compliant mechanism is investigated by simulation and experiments. The results indicate the composites trailing edge based compliant mechanism can approximately bend down 8 degrees and satisfies the design requirement.

Integrating superstructure‐based design of molecules, processes, and flowsheets

AbstractThe key to many chemical and energy conversion processes is the choice of the right molecule, for example, used as working fluid. However, the choice of the molecule is inherently coupled to the choice of the right process flowsheet. In this work, we integrate superstructure‐based flowsheet design into the design of processes and molecules. The thermodynamic properties of the molecule are modeled by the PC‐SAFT equation of state. Computer‐aided molecular design enables considering the molecular structure as degree of freedom in the process optimization. To consider the process flowsheet as additional degree of freedom, a superstructure of the process is used. The method results in the optimal molecule, process, and flowsheet. We demonstrate the method for the design of an organic Rankine cycle considering flowsheet options for regeneration, reheating, and turbine bleeding. The presented method provides a user‐friendly tool to solve the integrated design problem of processes, molecules, and process flowsheets.

Research on Satisfactory Integrated Design of Event-Triggered Fault Accommodation and Network Communication Saving for NCSs With Actuator Saturation Under Non-Uniform Transmission

Under the non-uniform transmission period, the satisfactory integrated design problem combining active fault-tolerant control and network communication saving was studied for nonlinear network control systems (NCSs) with actuator saturation constraints based on discrete event-triggered communication scheme (DETCS). First, the model of a non-uniform transmission closed-loop fault system was established, which includes the network attribute, actuator saturation constraints, estimation value of fault and state, event-triggered condition, disturbance information and so on. Second, the method of fault estimation with H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> -performance was proposed by a continuous time state observer. Furthermore, a satisfactory integrated design method integrating event-triggered fault accommodation and network communication saving was given for non-uniform transmission nonlinear NCSs with α-stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> /H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> performance. Finally, a MATLAB simulation was conducted to verify the effectiveness and feasibility of the proposed method based on a nonlinear NCS example. In order to reflect the real network transmission circumstances fully, a semi entity experimental platform was also built to verify the effectiveness and feasibility of the proposed method.

Integrated fault detection and control for two‐dimensional Markovian jump systems

SummaryThis paper is concerned with the problem of integrated fault detection and control for a class of two‐dimensional (2D) discrete‐time Markovian jump systems. The mathematical model of 2D Markovian jump systems is established upon the well‐known Roesser model, and a faults detection filter/controller is proposed to detect faults and meet some control specifications simultaneously. In this strategy, it takes into account both the fault detection objective and the control objective simultaneously through certain performance levels. The integrated design problem is then formulated as a multi‐objective optimization problem, which is nonconvex in essence. Furthermore, a two‐step algorithm is developed to solve this nonconvex problem. Sufficient conditions for existence of the desired fault detection filter/controller are established in terms of LMIs. A numerical example is used to demonstrate the effectiveness of the proposed method.

Integrated Fault Tolerant Control for Saturated Systems with Additive Faults: A Comparative Study of Saturation Models

In this paper, the integrated design problem of Fault Estimation (FE) and Fault Tolerant Control (FTC) for saturated systems is considered. The system suffers from input saturation and L2-bounded disturbances. To design an adaptive observer-based FE, the actuator output measurements are not used, when the actuator is saturated, there exist new interactions between FE and FTC. In such a case the separation principle for FE and FTC design does not hold anymore. In this paper, a method is introduced for integrated design of FE and FTC, which guarantees boundedness stability of such a system. To extract sufficient conditions for stability and minimum L2-gain performance for disturbance rejection, the Modified Sector Condition (MSC) is employed for saturation modeling. Also, Quadratic Polytopic Differential Inclusion (QPDI) approach is developed for the comparative study. All conditions are cast as Linear Matrix Inequality(LMIs) that can be evaluated in a single step. In a numerical example, the feasibility of the introduced method for stability guarantee is demonstrated and performance characteristics of FE and FTC in disturbance rejection are compared for both modeling approaches.

An aerothermodynamic design optimization framework for hypersonic vehicles

In the aviation field great interest is growing in passengers transportation at hypersonic speed. This requires, however, careful study of the enabling technologies necessary for the optimal design of hypersonic vehicles. In this framework, the present work reports on a highly integrated design environment that has been developed in order to provide an optimization loop for vehicle aerothermodynamic design. It includes modules for geometrical parametrization, automated data transfer between tools, automated execution of computational analysis codes, and design optimization methods. This optimization environment is exploited for the aerodynamic design of an unmanned hypersonic cruiser flying at M∞=8 and 30 km altitude. The original contribution of this work is mainly found in the capability of the developed optimization environment of working simultaneously on shape and topology of the aircraft. The results reported and discussed highlight interesting design capabilities, and promise extension to more challenging and realistic integrated aerothermodynamic design problems.

Overview of control-centric integrated design for hypersonic vehicles

Hypersonic vehicles (HSVs) exhibit significant advantages over other vehicles, including the wide range of velocity and large airspace types, and these features have contributed to the rapid development of HSVs in the last 20 years. Moreover, hypersonic technologies have become a multidisciplinary research topic in the fields of aerodynamics, propulsion, structure, material, and control. Different types of re-entry gliding, air-breathing cruise, and aerospace vehicles have been designed to realize ambitious tasks, which in turn influenced the technological advancements and process change in the military. This paper summarizes the control-oriented integrated design of HSVs. First, the status of current research on the distinct characteristics and technique issues of HSVs is introduced. Then, the progresses made on complex modeling, guidance and control, and trajectory optimization are elaborated to exhibit the significant research interest in hypersonic technologies. The control-integrated design of HSVs is emphasized to solve the multidisciplinary design problems associated with the model and its control and trajectory. Various strategies regarding the multidisciplinary optimization design are also proposed to solve the integrated design problem. Finally, suggestions are provided for the control-oriented integrated design of HSVs.

Comprehensive experimental design for chemical engineering processes: A two-layer iterative design approach

A systematic framework for optimal experimental design (OED) of multiple experimental factors is proposed to support data collection in chemical engineering systems with the purpose to obtain the most informative data for modeling. The structural identifiability is firstly investigated through a combined procedure with the generating series method and the identifiability tableau. Next the parameter estimability is analyzed via the orthogonalized sensitivity analysis in order to identify crucial and identifiable model parameters. Traditionally OED treats separate problems such as the choice of input conditions, the selection of variables to measure, and the design of sampling time profile. A new OED strategy is proposed that optimizes these interdependent factors in one framework. An iterative two-layer design structure is developed. In the lower layer for observation design, the sampling profile and the measurement set selection are combined and formulated as a single integrated observation design problem, which is relaxed to a convex optimization problem that can be solved with a local method. Thus the measurement set selection and the sampling profile can be determined simultaneously. In the upper layer for input design, the optimization of input intensities is obtained through stochastic global searching. In this way, the multi-factor optimization problem is solved through the integration of a stochastic method, for the upper layer, and a deterministic method, for the lower layer. Case studies are conducted on two biochemical systems with different complexities, one is an enzyme kinetically controlled synthesis system and the other one is a lab-scale enzymatic biodiesel production system. Numerical results demonstrate the effectiveness of this iterative double-layer OED optimization strategy in reducing parameter estimation uncertainties compared with conventional approaches.

Integrated design of ORC process and working fluid using process flowsheeting software and PC-SAFT

Organic Rankine Cycles (ORC) transform low-temperature heat into electrical power. To make best use of a heat source, ORC process and working fluid have to be optimized simultaneously. Thus, integrated design approaches of fluids and processes have been developed. However, integrated design approaches are usually complex and based on specific software tools which prevents fast and easy development of the ORC models. In this work, we have integrated the so-called 1-stage CoMT-CAMD approach into the process flowsheeting software gPROMS ProcessBuilder allowing for integrated design of process and working fluid. In 1-stage CoMT-CAMD, thermodynamic properties are modeled by the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state, which we use directly from the gSAFT physical property package. To introduce the molecular structure of the working fluid as an additional degree of freedom within the process optimization, we implemented the homosegmented group contribution approach of PC-SAFT and the Computer-aided Molecular Design (CAMD) formulation of 1-stage CoMT-CAMD in ProcessBuilder. Existing model libraries of ProcessBuilder were adapted to employ the Variable Molecular Structure Compound feature (VMSC) of gSAFT during process optimization. The resulting mixed integer nonlinear program (MINLP) optimization problem is solved by the standard MINLP solver integrated in ProcessBuilder. Thereby, the optimal working fluid and the corresponding optimal process are identified in one single optimization. The resulting tool enables the easy definition of integrated design problems based on the drag-and-drop feature of a process flowsheeting software for ORCs and beyond.