Hierarchical Design Methodology Research Articles

Crack-Deflecting Lattice Metamaterials Inspired by Precipitation Hardening.

Lattice structures, comprising nodes and struts arranged in an array, are renowned for their lightweight and unique mechanical deformation characteristics. Previous studies on lattice structures have revealed that failure often originates from stress concentration points and spreads throughout the material. This results in collapse failure, similar to the accumulation of damage at defects in metallic crystals. Here the precipitation hardening mechanism found in crystalline materials is employed to deflect the initial failure path, through the strategic placement of strengthening units at stress concentration points using the finite element method. Both the mesostructure, inspired by the arrangement of crystals, and the inherent microstructure of the base materials have played crucial roles in shaping the mechanical properties of the macro-lattices. As a result, a groundbreaking multiscale hierarchical design methodology, offering a spectrum of design concepts for engineering materials with desired properties is introduced.

Bio-inspired hierarchical honeycomb metastructures with superior mechanical properties

• A new honeycomb metastructure design methodology is inspired by the hierarchical idea found in nature. • The principles of conformal, hierarchy, number and size design are deduced. • A novel hierarchical honeycomb metastructure can improve energy absorption with other performances unchange. Inspired by the hierarchical macro and microstructures widely found in nature, this study proposes a novel hierarchical honeycomb design methodology. The aim is to overcome the shortcoming of conventional honeycomb structures that have poor energy absorption properties due to damage after loading. Thereby, a new honeycomb structure with several superior mechanical properties is obtained. Firstly, triangular, square, and circular holes are used at the third microstructure level. Moreover, their filling types, filling principles, and dimensional design basis are thoroughly investigated. And a hierarchical honeycomb is generated by arranging them on the cell walls of a conventional honeycomb according to the conformal design guidelines. Finally, the performance of the designed hierarchical honeycomb metastructure is analyzed and compared by simulation and experiment. It is found that the hierarchical honeycomb metastructures exhibit significantly improved overall mechanical properties compared with the conventional honeycomb structures. The hierarchical honeycomb metastructures with different holes have different performance enhancement effects on the conventional honeycomb structure. Among them, the hierarchical honeycomb metastructures with circular holes have the best performance improvement compared to conventional honeycomb structures. The hierarchical square honeycomb with circular holes has 0.84% stiffness loss, 19.38% strength loss, and 199.67% energy absorption performance improvement. However, the hierarchical hexagon honeycomb with circular holes has 1.06% stiffness improvement, 5.55% strength loss, and 345.24% energy absorption performance improvement. Additionally, the reliability of the novel honeycomb metastructure is verified to be better than the conventional honeycomb structure with the spacecraft return capsule shell.

Decision-making and control co-design for multi-agent systems: a hierarchical design methodology

Decision-making and control co-design for multi-agent systems: a hierarchical design methodology

Hierarchical Data Analysis for the Characterization of Polymeric Materials: Linking Measurements and Statistical Methodology

As future chemical engineers, it is important that students be able to identify and quantify sources of error. A statistical analysis technique that is often overlooked is hierarchical design methodology, which allows for the separation of overall variance into several related components. While hierarchical methodology is relevant to many fields, we have demonstrated that it can be taught through the synthesis and characterization of polymeric materials. Basic statistical concepts are described, along with relevant examples.

Plug-in hybrid electric buses total cost of ownership optimization at fleet level based on battery aging

In this paper a hierarchical energy management strategy design methodology for total cost of ownership management at fleet level is proposed. The decisions are taken from the fleet level point of view, to optimize the whole fleet based on the hierarchical decision maker and management, composed of three levels. The outer part is the offline route-to-bus data exploitation and decision maker, aiming to establish the dynamic programming optimization design. The next level is the offline optimization bus-to-route. Based on the previous decision, the neuro-fuzzy learns from the global optimal solutions. Finally, the trained fuzzy-logic strategy is used to manage the online operation. This fleet is re-organized and the online operation energy management strategy is updated throughout the bus lifetime. These decisions are made based on the evaluated battery lifetime of the fleet, with the aim to meet the planned total cost of ownership requirements. The total cost of ownership for the bus-to-route energy management strategy, has been improved a 7.65 % at fleet level against a charge-sustaining charge-depleting strategy. In the route-to-bus fleet re-organization and update, up to 5.51 % total cost of ownership improvement at fleet level has been obtained against not applying the fleet management.

Determining optimal granularity level of modular product with hierarchical clustering and modularity assessment

Modular product architecture is beneficial for the product maintenance, upgrade, components’ concurrent design through team work, and achieving the mass customization eventually. Recent researches tend to group elements into modules as a flat map, but this is inconsistent with the nested composition in product final assembly. Finding the hierarchical modular partition for elements of a product and obtaining its optimal granularity level are still necessary to ease the partition and combination for sub-design tasks. We use the design structure matrix (DSM) to represent the relationships among elements of a product. The hierarchical clustering functions such as pdist and linkage within MATLAB software are utilized to form the hierarchical dendrogram for DSM elements, and the modularity index Q is applied to assess the modular clustering results. The partitions are acquired by various distance threshold values in the vertical axis of the hierarchical dendrogram. The ‘cityblock’ and ‘average’ are found as preferred parameters for pdist and linkage functions, respectively, from loop test experiments. Combining the modularity formula in a research literature, a hierarchical modular architecture design methodology is proposed in this work to determine the optimal granularity level of a modular product and to provide solutions for designer selection. Case studies and comparisons in a benchmark problem and a concrete spraying machine illustrate the effectiveness and efficiency of the proposed method. It is characterized by being able to find stable modular partition results for both float and binary DSM elements and satisfying the recommended modular number rule simultaneously.

Cost-Effective Optimization Model for Transmission Line Outage Rate Control Due to Back-Flashover Phenomena

This paper presents a cost-effective optimization model for transmission line lightning performance design. The objective is to determine the appropriate insulation level and a particular grounding scheme of each support for a given line outage rate requirement due to the back-flashover phenomena at a minimum overall cost. To ensure a minimum global investment cost, the constraints associated with the individual lightning behavior of each tower section are relaxed depending on the regional atmospheric activity and on the particular characteristics of the soil, and therefore on the costs of the required grounding and insulation systems at each tower location, enforcing the appropriate lightning behavior of the complete transmission line. The proposed model is based upon a linear-integer programing problem formulation and solutions are obtained from the application of a three-layer hierarchical design methodology. The proposal has been tested in a 230 kV transmission line, 85.4 km long, with 180 towers. Results are presented and compared with designs obtained through by a conventional grounding optimization with important reductions in investment costs, encouraging the use and further development of the methodology.

Hierarchical System Design Using Refinable Recursive Petri Net

This paper is in the framework of the specification and verification of concurrent dynamic systems. For this purpose we propose the model of Refinable Recursive Petri Nets (RRPN) under a maximality semantics. In this model a notion of undefined transitions is considered. The underlying semantics model is the Maximality Abstract Labeled Transition System (AMLTS). Then, the model supports a definition of a hierarchical design methodology. The example of a cutting flame machine is used for illustrating the approach.

Design concept for coal-based polygeneration processes of chemicals and power with the lowest energy consumption for CO2 capture

Single coal based chemicals production processes emit large amount of CO2 during conversion of the syngas to the high H2/CO ratio feed gas for chemicals synthesis. However, the feed gas is with a low CO2 molar fraction, leading to high energy cost for CO2 capture. In this work, we try to reduce energy consumption for CO2 capture by improving its molar fraction. A new methanol and power polygeneration process is designed and analysed based on process modeling and simulation. The hierarchical conceptual design methodology is introduced to design the polygeneration more reasonably. In this process, the shifted syngas exiting from the water gas shift unit first goes into the CO2 capture unit to remove CO2. Then, the purified H2-rich syngas is mixed with the unshifted syngas and fed into the methanol synthesis to produce methanol. Then, unreacted syngas out from the methanol synthesis unit is moderately recycled to use, while the rest is used to generate power. Energy consumption for CO2 capture of the polygeneration process is 0.7 GJ/t-CO2, which is a 40.6% reduction compared to that of the single coal-to-methanol process and a 22.2% reduction to that of coal-to-hydrogen for power generation process. Techno-economic analysis shows that energy saving ratio and primary cost saving ratio are 16.5% and 13.2%, respectively.

A hierarchical approach to warehouse design

The design of large complex systems, such as warehouses, requires multiple experts and analyses as well as methods to organise and integrate their knowledge. While there are many models for optimising individual aspects of warehouses, there is not, today, a comprehensive design methodology that incorporates and supports all of the design decisions and provides a method to effectively integrate the solutions to these subproblems into a complete warehouse system specification. In this research, we propose a hierarchical design decision support methodology based on decomposing the design problem into a set of subproblems and using a formal model of the system to integrate the solutions to these subproblems. The methodology enables a thorough search of the design space and the identification of many candidate designs for consideration by the design decision maker. The hierarchical design methodology is demonstrated with an example of designing a forward pick area.

Cascade nonlinear feedforward-feedback control of stagnation pressure in a supersonic blowdown wind tunnel

Abstract Current trends in the development of control systems involve disproportionately high costs for embedded software integration and testing techniques that rely almost exclusively on exhaustive testing of more or less complete versions of complex systems. Wind tunnel control systems are not an exception. A formal methodology for supersonic flow control does not exist, which is not acceptable from a perspective of cost, reliability and safety of wind tunnel operations. The cascade nonlinear feedforward-feedback stagnation pressure controller proposed here is intended to address this deficiency in the operation of a supersonic blowdown wind tunnel. By focusing on a model-based approach using physical principles and hierarchical design methodologies, a systematic design method is offered for stagnation pressure control in particular, and control of flow parameters in general. The suggested mathematical model of supersonic flow in a blowdown wind tunnel is analyzed and main challenges of using a model-based approach are identified, with an emphasis on high process nonlinearity and an infinite number of possible operating conditions. The model is applied to the VTI Belgrade T-38 blowdown wind tunnel to identify the feedforward component that accurately predicts the nonlinear response of the facility. The Simulink® models of the facility and the proposed controller are developed to tune the feedback component in numerical simulations and verify the controller. The wind tunnel control system is implemented as an embedded distributed hierarchical system and experiments to verify the suggested control method are realized at Mach numbers 1.0–4.0. Both simulations and experiments demonstrate that feedback calculation successfully captures nonlinearities in the facility response, enabling a simple linear feedback controller with a single set of control terms to be used only to trim out additional deviations for an entire operating range of the facility. The feedforward-feedback architecture thus improves setpoint reference tracking, while the cascade architecture improves disturbance rejection performance compared to common single loop solutions. Combined within a single system, they eliminate large transient pressure overshoots typical for blowdown facilities, decrease the setpoint settling time and improve overall stagnation pressure control accuracy. In addition, system integration and testing time and costs are significantly reduced by analyzing physical properties of the process and taking them into consideration during early stages of the system development.

Hierarchical Design Method for Multi-Agent Systems

This paper proposes a new hierarchical design method for the specification and the verification of multi agent systems (MAS). For this purpose, the authors propose the model of Refinable Recursive Petri Nets (RRPN) under a maximality semantics. In this model, a notion of undefined transitions is considered. The underlying semantics model is the Abstract Maximality-based Labeled Transition System (AMLTS). Hence, the model supports a definition of a hierarchical design methodology. The example of goods transportation is used for illustrating the approach. For the system assessment, the properties are expressed in CTL logic and verified using the verification environment FOCOVE (Formal Concurrency Verification Environment).

A hierarchical fuzzy axiomatic design methodology for ergonomic compatibility evaluation of advanced manufacturing technology

Advanced manufacturing technology (AMT) is a relevant resource that has been extensively used in modern industries around the world with the aim of being competitive and maintaining high levels of quality and performance. There is a wide variety of tools and models available in the literature to support AMT selection and evaluation processes. Usually, they consist of analyses of tangible aspects, such as cost, time, speed, precision, among others; however, some other important aspects are commonly neglected, that is, the case of human factors and ergonomic characteristics. This paper presents a new methodology for the evaluation of ergonomic compatibility of AMT. This methodology may be considered as a decision aid; thus, decision makers might perform their duties in a more complete manner taking into account ergonomic attributes. Fuzzy axiomatic design applications are state of the art methods for decision making, and this paper contributes with a unique application for ergonomic compatibility evaluation for AMT. The first part of the paper presents the findings of an extensive literature review about important ergonomic attributes of AMT. Then, those attributes were originally structured following a multi-attribute axiomatic design approach for AMT ergonomic evaluation under a fuzzy environment. Also, a unique ergonomic compatibility survey was proposed for data collection and an original procedure was developed for AMT evaluation, a numerical example is provided. The ergonomic compatibility concept was tested and validated using the Cronbach's alpha test (α ≥ 0.7), finding that the instrument is suitable for the measurement of the proposed construct.

Bio-driven system-based virtual reality for prosthetic and rehabilitation systems

Current prosthetic and rehabilitation devices, used for those who are limbless or born with congenital defects or required rehabilitation, are difficult to use. The users have problems to adapt to their new hosts or receiving any bio-feedback despite rehabilitation process and retraining, particularly when working with electromyogram (EMG) signals. In characterizing virtual human limbs, as a potential prosthetic device in three dimensions (3D) virtual reality, patients are able to familiarize themselves with their new appendage and its capabilities or can see their movements’ intention in a Virtual Training Environment. This paper presents a virtual reality (VR)-based design and implementation of a below-shoulder 3D human arm capable of 10-class EMG-based motions driven system of biomedical EMG signal. The method considers a signal classification output as potential control stimulus to drive the virtual limb. A hierarchical design methodology is adopted based on anatomical structure to congruent with virtual reality modeling language (VRML) architecture used in order to progressively build the user interface model and its inherent functionality. The resulting simulation is based on a portable, self-contained VRML prototype implementation paired with an instrumental virtual control-select board capable of actuating any combinations of singular or paired kinematic of 10-class EMG motions. The simulation allows for multiple degree-of-freedom profiles as the classes can be activated independently, or in conjunction with others, allowing enhanced arm movement. Provisions for direct classified control inputs are built into the prototype for holistic system construction.

Hierarchical self-assembly of complex polyhedral microcontainers

The concept of self-assembly of a two-dimensional (2D) template to a three-dimensional (3D) structure has been suggested as a strategy to enable highly parallel fabrication of complex, patterned microstructures. We have previously studied the surface-tension-based self-assembly of patterned, microscale polyhedral containers (cubes, square pyramids and tetrahedral frusta). In this paper, we describe the observed hierarchical self-assembly of more complex, patterned polyhedral containers in the form of regular dodecahedra and octahedra. The hierarchical design methodology, combined with the use of self-correction mechanisms, was found to greatly reduce the propagation of self-assembly error that occurs in these more complex systems. It is a highly effective way to mass-produce patterned, complex 3D structures on the microscale and could also facilitate encapsulation of cargo in a parallel and cost-effective manner. Furthermore, the behavior that we have observed may be useful in the assembly of complex systems with large numbers of components.

Multi-domain simulation using VHDL-AMS for distributed MEMS in functional environment: Case of a 2D air-jet micromanipulator

In this paper, the authors report about recent achievement in distributed Micro Electro Mechanical Systems (MEMS) behavioral modeling, allowing both easy development and faster simulation for better integration of arrayed MEMS into systems. Design and simulation are produced by solver-based cost-effective solution using VHDL-AMS. A hierarchical circuit-level design methodology has been followed to model and simulate a MEMS array-based smart surface applied in air–fluid environment for 2D contactless micromanipulation. Using a V-shaped-based design approach, a top-down VHDL-AMS-based modeling has been first achieved with behavioral, structural behavioral, and component models, which include a MEMS-based pneumatic microactuator. Then, a modeling bottom-up approach has been developed to validate our design by comparing simulations and experiments of the distributed surface. Good agreements of resulting simulations have been successfully provided at all abstraction levels proving capability and facility of using VHDL-AMS for coupled distributed physical models.

Hierarchical Probabilistic Macromodeling for QCA Circuits

With the goal of building an hierarchical design methodology for quantum-dot cellular automata (QCA) circuits, we put forward a novel, theoretically sound, method for abstracting the behavior of circuit components in QCA circuit, such as majority logic, lines, wire-taps, cross-overs, inverters, and corners, using macromodels. Recognizing that the basic operation of QCA is probabilistic in nature, we propose probabilistic macromodels for standard QCA circuit elements based on conditional probability characterization, defined over the output states given the input states. Any circuit model is constructed by chaining together the individual logic element macromodels, forming a Bayesian network, defining a joint probability distribution over the whole circuit. We demonstrate three uses for these macromodel-based circuits. First, the probabilistic macromodels allow us to model the logical function of QCA circuits at an abstract level - the "circuit" level - above the current practice of layout level in a time and space efficient manner. We show that the circuit level model is orders of magnitude faster and requires less space than layout level models, making the design and testing of large QCA circuits efficient and relegating the costly full quantum-mechanical simulation of the temporal dynamics to a later stage in the design process. Second, the probabilistic macromodels abstract crucial device level characteristics such as polarization and low-energy error state configurations at the circuit level. We demonstrate how this macromodel-based circuit level representation can be used to infer the ground state probabilities, i.e., cell polarizations, a crucial QCA parameter. This allows us to study the thermal behavior of QCA circuits at a higher level of abstraction. Third, we demonstrate the use of these macromodels for error analysis. We show that low-energy state configurations of the macromodel circuit match those of the layout level, thus allowing us to isolate weak points in circuits design at the circuit level itself

A hierarchical design methodology for full-search block matching motion estimation

Many useful DSP algorithms have high dimensions and complex logic. Consequently, an efficient implementation of these algorithms on parallel processor arrays must involve a structured design methodology. Full-search block-matching motion estimation is one of those algorithms that can be developed using parallel processor arrays. In this paper, we present a hierarchical design methodology for the full-search block matching motion estimation. Our proposed methodology reduces the complexity of the algorithm into simpler steps and then explores the different possible design options at each step. Input data timing restrictions are taken into consideration as well as buffering requirements. A designer is able to modify system performance by selecting some of the algorithm variables for pipelining or broadcasting. Our proposed design strategy also allows the designer to study time and hardware complexities of computations at each level of the hierarchy. The resultant architecture allows easy modifications to the organization of data buffers and processing elements-their number, datapath pipelining, and complexity-to produce a system whose performance matches the video data sample rate requirements.

Lagrangian Coordination for Enhancing the Convergence of Analytical Target Cascading

DOI: 10.2514/1.15326 Analytical target cascading is a hierarchical multilevel multidisciplinary design methodology. In analytical target cascading, top-level design targets (i.e., specifications) are propagated to lower-level design problems in a consistent and efficient manner. In this paper, a modified Lagrangian dual formulation and coordination for analytical target cascadingaredevelopedtoenhanceaformulation andcoordinationproposedearlierintheliterature.Theproposed approach guarantees all the properties established earlier and additionally offers new significant advantages. As established previously for the convex case, the proposed analytical target cascading coordination converges to a global optimal solution with corresponding optimal Lagrange multipliers in the dual space. The Lagrange multipliers can be viewed as the weights for deviations in analytical target cascading formulations. Thus the proposed coordination algorithm finds the optimal solution and the optimal weights for the deviation terms simultaneously.Theenhancementallowsfortargetcascadingbetweenlevels,fortheuseofaugmentedLagrangianto improveconvergenceofthecoordinationalgorithm,andforpreventionofunboundedness.Aguidelinetosetthestep size for subgradient optimization when solving the Lagrangian dual problem is also proposed.

Refinement of actions for real-time concurrent systems with causal ambiguity

Refinement of actions is a core operation in the hierarchical design methodology for concurrent systems. In this paper, we develop an approach of action refinement for concurrent systems with not only the notation of real-time but also with causal ambiguity, which often exists and appears in real application areas. The systems are modeled in terms of a timed extension of bundle event structures with causal ambiguity. Under a certain partial order semantics, the behavior of the refined system can be inferred compositionally from the behavior of the original system and from the behavior of the systems used to refine actions with explicitly represented start points. A variant of a linear-time equivalence termed pomset trace equivalence and a variant of a branching-time equivalence termed history preserving bisimulation equivalence based on the partial order semantics are both congruences under the refinement. The refinement operation behaves thus well and meets the commonly expected properties.