Optimization Procedure Research Articles

The Impact of High-Rise Building Shapes on Wind Flow Characteristics and Energy Potential

In recent years, wind energy has become a potential source of low carbon energy. The shape of a building is a significant factor in aerodynamics, providing an opportunity for wind power control and wind energy proliferation. This research project aims to study the design of high-rise buildings and investigate how wind affects energy absorption by developing an aerodynamic optimization procedure (AOP) and using Computational Fluid Dynamics (CFD) in COMSOL Multiphysics. This study aimed to optimize the building shape for wind energy exploitation. Optimizing the building shape in the early stages of design enables the control of wind-induced loads and responses and reduces the energy demand in high-rise buildings, where resource consumption is higher than that in low-height buildings. This study used a three-dimensional CFD simulation of wind loading on tall buildings to optimize the building shape. This research will provide valuable insights for architects, engineers, and building developers to design and optimize high-rise buildings for wind energy exploitation, reduce the carbon footprint, and improve the energy efficiency of buildings.

Design and Performance Assessment of Base Isolated Structures Supplemented with Vibration Control Systems

This paper investigates the implementation of supplemental vibration control systems (VCS) in base isolated (BI) structures, to improve their dynamic performance. More specifically, the aim of the VCS is to reduce the base displacement demand of BI structures, and at the same time mitigate the superstructure seismic responses. The purpose of the examined VCS is dual, and for this reason a multi-objective optimization methodology is formulated for the design of the VCS. The examined vibration absorbers include modifications of the KDamper concept. The KDamper is an extension of the traditional Tuned Mass Damper (TMD), and introduces a negative stiffness (NS) element to the additional oscillating mass of the TMD. The generated NS force is exactly in phase with the inertia force of the added mass, thus, artificially amplifying it. This way, lighter configurations are possible with an enhanced damping behavior. These VCS are designed based on engineering criteria and manufacturing constraints, while the excitation input used in the multi-objective optimization procedure is selected from a dataset of artificial accelerograms, designed to be spectrum-compatible with the EC8 design acceleration response spectrum. The effectiveness of the examined VCS is also assess with real near-fault earthquake records, and a comparison is performed with TMD-based VCS having 50 times larger additional masses. The numerical results demonstrate the superiority of the KDamper-based VCS in improving the dynamic behavior of BI structures over other mass-related systems (TMD).

Continuous Space Wireless Communication Tower Placement by Hybrid Simulated Annealing

Wireless communication tower placement arises in many real-world applications. This paper investigates a new emerging wireless communication tower placement problem, namely, continuous space wireless communication tower placement. Unlike existing wireless communication tower placement problems, which are discrete computational problems, this new wireless communication tower placement problem is a continuous space computational problem. In this paper, we formulate the new wireless communication tower placement problem and propose a hybrid simulated annealing algorithm that can take advantage of the powerful exploration capacity of simulated annealing and the strong exploitation capacity of a local optimization procedure. We also demonstrate through experiments the effectiveness of this hybridization technique and the good performance and scalability of the hybrid simulated annulling in this paper.

Reverse Engineering of Radical Polymerizations by Multi-Objective Optimization.

Reverse engineering is applied to identify optimum polymerization conditions for the synthesis of polymers with pre-defined properties. The proposed approach uses multi-objective optimization (MOO) and provides multiple candidate polymerization procedures to achieve the targeted polymer property. The objectives for optimization include the maximal similarity of molar mass distributions (MMDs) compared to the target MMDs, a minimal reaction time, and maximal monomer conversion. The method is tested for vinyl acetate radical polymerizations and can be adopted to other monomers. The data for the optimization procedure are generated by an in-house-developed kinetic Monte-Carlo (kMC) simulator for a selected recipe search space. The proposed reverse engineering algorithm comprises several steps: kMC simulations for the selected recipe search space to derive initial data, performing MOO for a targeted MMD, and the identification of the Pareto optimal space. The last step uses a weighted sum optimization function to calculate the weighted score of each candidate polymerization condition. To decrease the execution time, clustering of the search space based on MMDs is applied. The performance of the proposed approach is tested for various target MMDs. The suggested MOO-based reverse engineering provides multiple recipe candidates depending on competing objectives.

GRID-STEP OPTIMIZATION OF THE PARAMETERS OF THERMAL IMPACT ON THE TECHNICAL SYSTEM

The article solves applied problems of optimizing the parameters of technical systems under the influence of concentrated, discrete sources of thermal load. To improve the accuracy and speed of solving applied optimization problems, the authors propose a generalized procedure for finding the optimal thermal load parameters. This procedure consists of well-known computational methods for solving boundary value problems and ensuring the optimization of the objective function and its parameters. To calculate the values of the temperature field, it is necessary to solve a nonlocal boundary value problem of a system of nonlinear differential heat transfer equations. In order to find the conditions for the correctness of boundary value problems, the authors used the theory of pseudo-differential operators in the space of generalized slow power functions. This made it possible to guarantee the correctness of computational and applied optimization mathematical models. The procedure for grid-step optimization of the parameters of thermal action on a multilayer material proposed by the authors is based on a grid approach with discretization of the main parameters of thermal load and grinding of a large uniform grid in the vicinity of the selected node of the large grid. The directed search for local extremes of the mesh model is carried out by the nodes of the crushed mesh. The search for local extrema is performed by selecting the next node of a large grid. This approach will increase the accuracy of solving applied optimization problems by allowing further mesh refinement and refinement of the values of local extremes, and, consequently, refinement of the values of the global extremum of the objective function. The optimization of the thermal impact parameters was carried out according to the criterion of reducing damage to the test material. This makes it possible to increase the accuracy of the technological process of thermal action on a multilayer material.

Small animal patient preoperative preparation: a review of common antiseptics, comparison studies, and resistance.

This review aims to describe commonly used antiseptics in veterinary medicine including their mechanism of action, spectrum of activity, potential adverse effects, and application techniques. Additionally, it provides a review of the veterinary literature comparing antiseptics, a discussion of effectiveness and efficacy studies, and the potential for increased resistance to biocides and antimicrobials. This review concludes that appropriate selection and use is necessary to prevent the occurrence of surgical site infections, adverse effects, and potential for increasing resistance to antimicrobials. Continued research is needed to fill gaps in the current knowledge such as optimal preparation procedures for various surgical sites, standardization of efficacy and effectiveness testing, and the clinical impact of decreased susceptibility to chlorhexidine and other antiseptics.

Head and neck reconstruction with the superficial circumflex iliac artery perforator (SCIP) free flap: Lessons learned after 73 cases.

Head and neck tissue defects after ablative surgery often require complex and composite reconstructions. The superficial circumflex iliac artery perforator (SCIP) flap is an extremely versatile perforator-based flap with minimal donor site morbidity, which may represent the optimal procedure in this setting. Over the last 5 years, we collected a large base of experience, including both simple and chimeric SCIP-based reconstruction, making this flap our first choice for head and neck reconstructions. Seventy-three patients undergoing ablative head and neck surgery for oncologic pathologies were treated by means of a SCIP flap reconstruction. Patients' mean age was 67 years old (range 37-89), 51 were males and 22 were females. Fifty-eight flaps were simple and 15 were chimeric reconstruction patterns. Indocyanine green perfusion imaging was performed in all cases. All the patients were successfully treated with no flap losses were encountered. Twelve patients encountered postoperative complications: in four cases revision surgery was required for venous congestion, while the remaining cases were managed conservatively (four wound dehiscence and three infections). No patients showed donor site complications. The mean follow-up period was 11 months (range 3-24). Our case series demonstrates the reliability and versatility of the SCIP flap for different kinds of head and neck reconstructions. The chimeric options combined with bone, double skin paddle, and muscle offer a broad variety of functional reconstructive solutions for complex head and neck surgeries. Intraoperative indocyanine green perfusion examination provides a valuable tool to assess and ascertain proper vascularization and post-anastomosis vessel patency in complex microvascular flap-based reconstructions.

Online identification of Hammerstein systems with B‐spline networks

SummaryNonlinear systems widely exist in real‐word applications and the research for these systems has enjoyed a long and fruitful history, including the system identification community. However, the modeling for nonlinear systems is often quite challenging and still remains many unresolved questions. This article considers the online identification issue of Hammerstein systems, whose nonlinear static function is modeled by a B‐spline network. First, the identification model of the studied system is constructed using the bilinear parameter decomposition model. Second, the online recursive algorithms are proposed to find the estimates using the moving data window and the particle swarm optimization procedure, and show that these estimates converge to their true values with a low computational burden. Numerical examples are also given to test the effectiveness of the proposed algorithms.

Optimizing the Thickness of Functionally Graded Lattice Structures for High-Performance Energy Absorption: A Case Study Based on a Bicycle Helmet

This study explores the complete production chain of designing, optimizing, and Additive Manufacturing (AM) of a helmet incorporating a functionally graded lattice structure (FGLS). The potential of FGLSs in impact energy absorption tasks is investigated, along with the demonstration of a novel lattice optimization approach. Fifteen conformal, strut-based lattices are implemented in a realistic mountain bike helmet geometry and simulated in a standardized impact scenario in accordance with EN 1078. One model is subjected to the optimization procedure, produced, and physically tested. The study addresses limitations in prior research, emphasizing manufacturability in an AM context, lattice type exploration, the comparability of different unit cell types, and numerical modeling choices. The findings provide insights into the performance of lattice structures during impact, emphasizing practical engineering aspects such as design choices, optimization approaches, and manufacturing constraints.

A variable neighbourhood search for minimization of operation times through warehouse layout optimization

Abstract For companies involved in the supply chain, proper warehousing management is crucial. Warehouse layout arrangement and operation play a critical role in a company’s ability to maintain and improve its competitiveness. Reducing costs and increasing efficiency are two of the most crucial warehousing goals. Deciding on the best warehouse layout is a remarkable optimization problem. This paper uses an optimization method to set bin allocations within an automated warehouse with particular characteristics. The warehouse’s initial layout and the automated platforms limit the search and define the time required to move goods within the warehouse. With the help of historical data and the definition of the time needed to move goods, a mathematical model of warehouse operation was created. An optimization procedure based on the well-known Variable Neighbourhood Search algorithm is defined and applied to the problem. Experimental results demonstrate increments in the efficiency of warehousing operations.

Multi-objective seismic optimization and evaluation of core-damper-frame tall buildings considering SSI effect

To control the seismic response of the core-frame (CF) structure and attenuate the stress level of the core tube, a novel core-damper-frame (CDF) system is proposed by decoupling the perimeter frame and the central core with flexible damper connectors. In this way, the large inertia force of the perimeter frame cannot be fully transmitted to the core, and the stress of the core is mitigated. In the meantime, the damper connectors would absorb a considerable amount of seismic energy, protecting the perimeter frame as the relative displacement between the two subsystems (perimeter frame and core tube) occurs. By incorporating the soil-structure-interaction (SSI) and the filtered Gaussian white-noise excitation model, the "excitation-soil-core-damper-frame" augmented system is established. Combing the augmented system and the genetic algorithm, a stochastic optimization procedure of the CDF considering the SSI effect is proposed. The optimization aims to minimize a series of performance objectives including displacement, acceleration, shear force, and overturning moment of the CDF system. The conflicting relationships between the multiple objectives are discussed; the influence of the SSI effect and the excitation parameters are evaluated. From an illustrative 40-story CDF structural example, the system shows great superiority in controlling the higher mode vibrations, and could significantly reduce the peak core acceleration (by 54.44 %), frame acceleration (by 56.48 %), core drift (by 28.83 %), frame drift (by 39.28 %), core shear (by 83.67 %), and frame moment (by 22.41 %), as compared to its conventional CF counterpart. In special, over 50 % of the input seismic energy is dissipated by the damper connectors in the CDF system.

Automated cleaning of tie point clouds following USGS guidelines in Agisoft Metashape professional (ver. 2.1.0)

The U.S. Geological Survey (USGS) has published a guideline to improve the quality of digital photogrammetric reconstructions created with the widely used Agisoft Metashape Professional software. The suggested workflows aim at filtering out low-quality tie points from the tie point cloud to optimize the camera model. However, the optimization procedure relies on an iteratively performed trial-and-error approach. If manually performed, the time expenditure required from the operator can be significant and the optimization process can be affected by the degree of diligence that is applied.To minimize the time expenditure and attentiveness required from the operator and to provide a framework for an improved reproducibility of camera model optimization workflows, we present here a python script serving as an extension for Agisoft Metashape Professional (tested on version 2.1.0) that automatizes the iterative point filtering procedure proposed by the USGS. As a result, the entire processing cycle can be performed largely unattended.•A graphical user interface allows to individually adjust important camera model optimization parameters.•Main tie point cloud quality measures can be directly assessed.•The reproducibility of the automated camera model optimization as tested in this study generally is above 99%.

Optimal Constrained Groove Pressing Process Parameters Applying Modified Taguchi Technique and Multi-Objective Optimization

Most engineering problems are complicated, and developing mathematical models for such problems requires understanding the phenomena through experiments. It is well known that as processing parameters with assigned levels increase, so does the number of experiments. By minimizing the number of experiments, Taguchi’s method of experimental design will help to furnish the idea of full factorial experimental design. Taguchi’s method is more appropriate for single-objective optimization problems and needs modifications while dealing with multi-objective optimization problems. Aluminum alloys are in great demand in today’s automotive and aerospace sectors due to their low density, good corrosion resistance, and excellent machinability. The material is subjected to a constrained groove pressing (CGP) process to obtain microstructural grain refinement with enhanced mechanical behavior. This paper considers AA6061 material having major alloys such as silicon and magnesium. For this work, 3 CGP process parameters (viz., displacement rate, plate thickness and number of passes) are assigned 3 levels to each parameter, acquired the test data, viz., grain size (gs), micro hardness (hs), and tensile strength (ult) based on L9 orthogonal array of Taguchi. Using a modified version of Taguchi’s methodology, it is possible to estimate the range of grain size (gs), micro hardness (hs), and tensile strength (σult) for effective combinations of the CGP processing parameters and validate the results with existing test data. A more dependable and simpler multi-objective optimization procedure is used to choose the optimal CGP processing parameters.

An ensemble of artificial neural network models to forecast hourly energy demand

AbstractWe propose an ensemble artificial neural network (EANN) methodology for predicting the day ahead energy demand of a district heating operator (DHO). Specifically, at the end of one day, we forecast the energy demand for each of the 24 h of the next day. Our methodology combines three artificial neural network (ANN) models, each capturing a different aspect of the predicted time series. In particular, the outcomes of the three ANN models are combined into a single forecast. This is done using a sequential ordered optimization procedure that establishes the weights of three models in the final output. We validate our EANN methodology using data obtained from a A2A, which is one of the major DHOs in Italy. The data pertains to a major metropolitan area in Northern Italy. We compared the performance of our EANN with the method currently used by the DHO, which is based on multiple linear regression requiring expert intervention. Furthermore, we compared our EANN with the state-of-the-art seasonal autoregressive integrated moving average and Echo State Network models. The results show that our EANN achieves better performance than the other three methods, both in terms of mean absolute percentage error (MAPE) and maximum absolute percentage error. Moreover, we demonstrate that the EANN produces good quality results for longer forecasting horizons. Finally, we note that the EANN is characterised by simplicity, as it requires little tuning of a handful of parameters. This simplicity facilitates its replicability in other cases.

The use of real-world data for clinical investigation of effectiveness in drug development

ABSTRACT With the growing interest in leveraging real-world data (RWD) to support effectiveness evaluations for new indications, new target populations, and post-market performance, the United States Food and Drug Administration has published several guidance documents on RWD sources and real-world studies (RWS) to assist sponsors in generating credible real-world evidence (RWE). Meanwhile, the randomized controlled trial (RCT) remains the gold standard in drug evaluation. Along this line, we propose a hybrid two-stage adaptive design to evaluate effectiveness based on evidence from both RCT and RWS. At the first stage, a typical non-inferiority test is conducted using RCT data to test for not-ineffectiveness. Once not-ineffectiveness is established, the study proceeds to the second stage to conduct an RWS and test for effectiveness using integrated information from RCT and RWD. The composite likelihood approach is implemented as a down-weighing strategy to account for the impact of high variability in RWS population. An optimal sample size determination procedure for RCT and RWS is introduced, aiming to achieve the minimal expected sample size. Through extensive numerical study, the proposed design demonstrates the ability to control type I error inflation in most cases and consistently maintain statistical power above the desired level. In general, this RCT/RWS hybrid two-stage adaptive design is beneficial for effectiveness evaluations in drug development, especially for oncology and rare diseases.

D3S: Decision support system for sectorization

Sectorization problems refer to dividing a large set, area or network into smaller parts concerning one or more objectives. A decision support system (DSS) is a relevant tool for solving these problems, improving optimisation procedures, and finding feasible solutions more efficiently. This paper presents a new web-based Decision Support System for Sectorization (D3S). D3S is designed to solve sectorization problems in various areas, such as school and health districting,planning sales territories and maintenance operations zones, or political districting. Due to its generic design, D3S bridges the gap between sectorization problems and a state-of-the-art decision support tool. The paper aims to present the generic and technical attributes of D3S by providing detailed information regarding the problem-solution approach (based on Evolutionary Algorithms), objectives (most common in sectorization), constraints, structure and performance.

Development of an automated and cost-effective apparatus for sol-gel solution deposition using spray coating technique and its application for TiO[formula omitted]-based photocatalytic films

This study presents the development of a novel apparatus for automated sol–gel solution deposition through a cost-effective spray coating technique. The focus was on producing TiO2 films for photocatalytic applications, addressing environmental pollution and energy scarcity issues. The apparatus, constructed using economical materials, facilitated the production of TiO2 films with an anatase-like crystalline structure and uniform surface morphology. The methodology included detailed experimental procedures for solution preparation, substrate cleansing, and deposition process optimization. Characterization techniques such as scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), thermogravimetric analysis (TGA), X-ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FTIR), and UV–Vis spectroscopy were employed to assess the structural, morphological, and optical properties of the films. The results indicated the successful synthesis of anatase-phase TiO2 thin films with desirable optical properties and efficient photocatalytic activity, as demonstrated through the degradation of methylene blue and methyl orange. The study highlights the apparatus’s efficiency, versatility, and potential for industrial-scale production, thus offering promising prospects for practical applications and commercialization in the field of sustainable environmental solutions.

Practical Design Guidelines for Topology Optimization of Flexible Mechanisms: A Comparison between Weakly Coupled Methods

Industrial robots are complex systems, as they require the integration of several sub-assemblies to perform accurate operations. Moreover, they may experience remarkable dynamic actions due to high kinematic requirements, which are necessary to obtain reduced cycle times. The dynamic design of industrial robots can therefore be demanding, since the single structural component can induce an impact both in the design phase (development strategy and computational time) and at the machine level (global stiffness and natural frequencies). To this end, the present paper proposes first a topology optimization procedure based on the Equivalent Static Loads (ESL) method that integrates flexible multibody simulation outputs. The same procedure also foresees an intermediate static reduction to reduce and to precisely define the application points of the ESL. Secondly, an optimization procedure based on the Quasi-Static Loads (QSL) method integrating flexible multibody simulation outputs is proposed as well. The objective is to carry out a comparison between the two methods and consequently evaluate the benefits and drawbacks of the two. In the end, practical guidelines regarding the selection and application of the two methods are also provided to the reader.

Proposing a procedure for multi-objective optimization of cascade thermoelectric coolers to achieve maximum cooling capacity and COP

Abstract A novel approach is proposed for optimal designing two-stage thermoelectric coolers using the biogeography-based optimization algorithm. For the comprehensiveness of the research, both types of two-stage coolers, including electrically serial and separated stages, have been investigated. Using the proposed procedure, first by selecting the most important performance parameters of the cooler, i.e. COP and the cooling capacity as objective functions, the efficiency and the validity of the approach are proved by comparing the results with results of the previous researchers. In all the examined cases, the proposed approach has led to the enhancing of the cooler performance. The results of single-objective optimization showed that using the proposed method, the cooling capacity and COP can be improved up to 17 % and 8.5 % compared to the previous designs, respectively. In the following, multi-objective optimization of thermoelectric coolers is conducted, taking into account both the objectives of the COP and the cooling capacity. Finally, Pareto optimal solutions and the exergetic efficiency of the optimized cooler were calculated for different values of the weight factor of the multi-objective function. The results of multi-objective optimization showed that by increasing the COP weight factor in the objective function, the exergetic efficiency of the refrigeration system enhances.

Evaluation of the impact of breast-conserving surgery on cancer outcomes of multiple (multifocal or multicentric) ipsilateral breast cancer

Background Breast conservative therapy (BCT) includes conservative breast surgery (CBS) with adjuvant radiotherapy and is now considered a standard treatment for early-stage breast cancer to achieve survival with acceptable aesthetic outcomes. Management of multiple ipsilateral breast cancer (MIBC) is a challenge, since the choice of optimal surgical procedures is controversial. Recently, many breast surgeons have advocated CBS is technically feasible to safely excise MIBC in selected cases. Aim This study aimed to evaluate the outcome of MIBC patients who received CBS with special attention on local control and recurrence. Patient and method This retrospective study was carried out on 90 patients at Al Azhar University Hospital and Ain Shams University Hospitals between January 2021 and January 2023. Results The majority of patients 85 (94.4%) had two foci of disease while five (5.5%) patients had three foci. The distance between the lesions ranges between 0.5 and 6.5 cm. The most common type of CBS was wide local excision en bloc resection of all lesions with normal tissue in between was done in 85 (94.4%) patients and five (5.5%) patients had two separate incisions leaving normal tissue in between. Clear margins were reported in 79 (87.7%) patients. 15 (5.5%) patients had different pathological lesion types (heterogeneous). One patient had a recurrence and another had distant metastases. Conclusion With good patient selection, there is no difference between CBS and mastectomy in the management of MIBC. CBS is oncological safe provided that an adequate excision with clear margins followed by whole-breast radiation therapy and adjuvant systemic therapy.