Cost-effective Design Research Articles

Real-Time Acoustic Measurement System for Cutting-Tool Analysis During Stainless Steel Machining

This study presents a sound-based tool-wear monitoring system designed to overcome the limitations of conventional methods that focus solely on gradual and predictable wear patterns. The proposed system employs low-cost, high-frequency microphones and advanced signal processing—featuring analog/digital filtering, oversampling, signal conditioning, PLL-based synchronization, and feature extraction (ZCR, RMS)—to capture acoustic emissions during machining. Key innovations include optimized microphone placement, a custom PCB, and real-time data transfer via WiFi to MATLAB for analysis. Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. Tested on EN 1.4307 (AISI/ASTM 304L) stainless steel, the system demonstrated robust performance in real-time tool-condition assessment. Its scalable and cost-effective design allows for the integration of additional sensors and features, providing a non-invasive and adaptive solution to enhance machining efficiency and reduce operational costs.

Wave forces and dynamic pressures on pile-supported breakwaters with inclined perforated plates under regular waves

The use of pile-supported breakwaters can be a cost-effective solution for wave energy dissipation when traditional rubble mound breakwaters are not suitable. For a cost-effective design of these barriers, it is essential to obtain accurate estimates of dynamic pressures and wave forces. Laboratory experiments were conducted to investigate the dynamic pressures and forces on a novel pile-supported breakwater with inclined perforated plates. The analysis focused on various wave and structural parameters, including incident wave height, wave period, plate porosity, and plate configuration. For double-layer configurations with the same porosity, dynamic pressures on the single-layer or front plate were significantly higher than on the rear plate, with rear plate forces being 20% to 60% less. The dynamic pressure on the rear plate exhibited a uniform vertical distribution. Varying plate porosity at different locations significantly impacted structural forces. Gradually decreasing porosity improved wave dissipation and reduced forces on the plates, with front and back plate forces reaching approximately 70% of those on single-layer plates. Optimal protection across various wave periods can be achieved by adjusting porosity and plate arrangement. These findings provide valuable insights for designing pile-supported breakwaters in coastal protection engineering.

Risk−Based Cost−Benefit Optimization Design for Steel Frame Structures to Resist Progressive Collapse

The design of structures to resist progressive collapse primarily focuses on enhancing structural safety and robustness. However, given the low probability of accidental events, such designs often lead to a negative cost–benefit. To address this problem, this paper uses risk analysis to optimize the progressive collapse resistance design of steel frame structures. The elements’ cross-section design for the progressive collapse resistance of steel frame structures is optimized using genetic algorithms and SAP2000 23, which identify the structural model with the minimum robustness index while ensuring safety. The results show that the risk-based robustness index can effectively assess the cost of progressive collapse design. More importantly, the optimization model can rapidly identify the most cost-effective structural design solution that complies with progressive collapse resistance guidelines, enhancing the simplicity and usability of the structure design optimization process. Additionally, the integration of the SAP2000 API with Python 3.8 automation streamlines the parameterization process, minimizes manual errors, and enhances the precision and efficiency of the structural design optimization. Finally, the model’s effectiveness is validated through a case study, where the refined single-frame structure shows a reduction in initial construction and collapse-related costs by 2.4% and 9.1%, respectively. Meanwhile, the three-dimensional frame shows a 2.9% rise in initial costs but a 13.5% decrease in total collapse-resistant design costs, illustrating the model’s ability to balance safety with cost-effectiveness.

Technology roadmap toward the completion of whole-brain architecture with BRA-driven development

The development of brain-morphic software holds significant promise for creating artificial general intelligence that exhibits high affinity and interpretability for humans and also offers substantial benefits for medical applications. To facilitate this, creating Brain Reference Architecture (BRA) data, serving as a design specification for brain-morphic software is imperative. BRA-driven development, which utilizes Brain Information Flow (BIF) diagrams based on mesoscale brain anatomy and Hypothetical Component Diagrams (HCD) for corresponding computational functionalities, has been proposed to address this need. This methodology formalizes identifying possible functional structures by leveraging existing, albeit insufficient, neuroscientific knowledge. However, applying this methodology across the entire brain, thereby creating a Whole Brain Reference Architecture (WBRA), represents a significant research and development challenge due to its scale and complexity. Technology roadmaps have been introduced as a strategic tool to guide discussion, management, and distribution of resources within such expansive research and development activities. These roadmaps proposed a manual, anatomically based approach to incrementally construct BIF and HCD, thereby systematically expanding brain organ coverage towards achieving a complete WBRA. Large Language Model (LLM) technologies have introduced a paradigm shift, substantially automating the BRA-driven development process. This is largely due to the BRA data being structured around the brain’s anatomy and described in natural language, which aligns well with the capabilities of LLMs for supporting and automating the construction and verification processes. In this paper, we propose a novel technology roadmap to largely automate the creation of WBRA, leveraging neuroscientific insights. This roadmap includes 12 activities for automating BIF construction, notably extracting anatomical structures from scholarly articles. Furthermore, it details 11 activities aimed at enhancing the integration of Hypothetical Component Diagrams (HCD) into the WBRA, focusing on automating checks for functional consistency. This roadmap aims to establish a cost-effective and efficient design process for WBRA, ensuring the availability of brain-morphic software design specifications that are continually validated against the latest neuroscientific knowledge.

Towards a durable and sustainable warm mix asphalt: techno-economic and environmental evaluation considering balanced mix design approach

In response to the worldwide inclination towards sustainability and circular economy targets, there is a need to employ innovative and eco-friendly paving technologies. This research aims to investigate the mechanical performance (rutting and cracking resistance) and durability characteristics (resistance against moisture susceptibility) of long-term aged warm mix asphalt (WMA) mixtures containing reclaimed asphalt pavement (RAP), a WMA additive, an anti-stripping agent, and three chemically different recycling agents (RA) (an aromatic extract (A), a triglyceride/fatty acid (TF), and a tall oil (T)) through conducting the semi-circular bending (SCB) fracture, dynamic creep (DC), and indirect tensile strength (ITS) tests. Then, two-dimensional (2-D) and three-dimensional (3-D) performance interaction diagrams (PID) were used to identify asphalt mixtures with satisfactory performance in terms of moisture susceptibility, rutting failure, and fatigue cracking. Furthermore, an integrated environmental-economic comparison of the mixtures was conducted using a sustainability rating system developed by the authors. This system aims to identify cost-effective asphalt mix designs with lower CO2 equivalent emissions. The results of mechanical properties and Tukey’s honest significant difference (HSD) analysis indicated that the performance of RAP-blended mixtures is superior or equal to the performance of the mixtures without RAP when modified with RAs, WMA additive, and anti-stripping agent. Furthermore, the long-term aging performance of WMA mixtures containing RAP was significantly influenced by the RA' type. Results of economic and environmental analyses also indicated that virgin asphalt binder contributed the most to both cost burden and Greenhouse Gas (GHG) emissions, accounting for an average of 60% of the total cost and 45% of the total GHG emissions during the material and mixture production phase. Therefore, RAP recycling which decreases the need for virgin asphalt binder in addition to being replaced by a part of the required virgin aggregates is considered as one of the extremely environmentally friendly and cost-effective strategies. The environmental impacts of asphalt mixtures are significantly influenced by the choice of RAs, particularly when using a high RAP content. This study suggests that the utilization of tall oil and aromatic extract, as demonstrated, could be a better choice from an environmental perspective.

Interlaminar toughening and self-healing mechanism for hard-and-soft layered composite laminates

This paper finds a simple and cost-effective design to create high interlaminar toughness and self-healing Euplectella Aspergillum based bio-inspired composite laminates with thermoplastic polymer poly(ethylene-co-methacrylic acid) (EMAA). Three different configuration strategies containing hard/soft structures are proposed and mode I interlaminar toughness is determined to investigate the toughening effect and self-healing behavior. The results show that configuration and fiber types have great influence on toughening and self-healing efficiency. The novel configuration can achieve an improvement of over 600% in toughness for carbon fiber reinforced plastic (CFRP) and close to 100% for healing efficiency in the case of glass fiber reinforced plastic (GFRP) laminates. All the proposed configurations eliminate unstable delamination crack propagation process observed in CFRP woven laminates. In addition, repeated self-healing behavior is studied and self-healing efficiency remains stable after three damage-healing cycles. This study reveals toughening and self-healing behaviors of different configurations and provides novel strategies for laminate design.

Clinical Utility of a Novel Triplex Digital PCR Assay for Clone Monitoring in Sequential and Relapsed Pediatric B-Cell Acute Lymphoblastic Leukemia Patients.

Digital polymerase chain reaction (PCR) studies for clonal disease monitoring in B-acute lymphoblastic leukemia patients are currently limited due to the heterogeneous nature of mutations, which limit cost-effective assay designs. In this study, 70 samples (14 relapse and 56 sequential therapy samples) were tested for 13 recurrent mutations identified on deep sequencing in our published cohort (KRAS, NRAS, NT5C2, PMS2, UHRF1, KMT2D, and TP53 genes) via a novel triplex digital PCR assay. A total of seven major clones of NRAS [five] and NT5C2 [two] were noted in six out of 14 (43%) relapse patients, accounting for 44% of early relapses. In addition, 10 minor clones (PMS2 [two], NRAS [four], NT5C2 [three], and TP53 [one]) were noted in five out of 14 (36%) patients. In the 56 sequential therapy samples, six major clones were noted (NRAS [five], KRAS [one]) in four out of 14 (28.5%) patients, with two increasing in size in maintenance samples, leading to subsequent relapse in both cases. In addition, therapy-acquired minor clones in NT5C2 [four] and PMS2 [one] were seen to emerge in maintenance samples in four out of 14 (28.5%) patients, with concordant detection of such major and minor clones in unpaired relapse samples, indicating the need for their active surveillance during therapy. Overall, digital PCR validated NRAS and NT5C2 major clones in one-third (10 out of 27; 37%) of cases, driving nearly half of early relapses.

Optimal Design of Rectangular Tank Walls With Ribs Using Numerical Models and Global Optimization

This paper addresses the optimization of the cross-section in rectangular above-ground tank walls, incorporating vertical ribs and an optional top ring. The objective is to minimize the volume of concrete used, while maintaining key performance criteria such as keeping the maximum tensile stress below the material’s allowable limit and minimizing deflections. The analysis is performed using the finite element method (FEM), with the optimization handled through a local gradient-based algorithm (trust region method), supported by a multistart technique to navigate the complexity of the design space and avoid suboptimal solutions. The results demonstrate that this approach effectively reduces concrete consumption without exceeding the tensile stress limits or causing excessive deflection, offering more efficient and cost-effective designs for rectangular tanks used in water storage applications. This method provides valuable insights into the balance between material usage and performance constraints, contributing to sustainable engineering practices.

Improvement in an Analytical Approach for Modeling the Melting Process in Single-Screw Extruders.

Most single-screw extruders used in the plastics processing industry are plasticizing extruders, designed to melt solid pellets or powders within the screw channel during processing. In many cases, the efficiency of the melting process acts as the primary throughput-limiting factor. If the material melts too late in the process, it may not be sufficiently mixed, resulting in substandard product quality. Accurate prediction of the melting process is therefore essential for efficient and cost-effective machine design. A practical method for engineers is the modeling of the melting process using mathematical-physical models that can be solved without complex numerical methods. These models enable rapid calculations while still providing sufficient predictive accuracy. This study revisits the modified Tadmor model by Potente, which describes the melting process and predicts the delay-zone length, extending from the hopper front edge to the point of melt pool formation. Based on extensive experimental investigations, this model is adapted by redefining the flow temperatures at the phase boundary and accounting for surface porosity at the beginning of the melting zone. Additionally, the effect of variable solid bed dynamics on model accuracy is examined. Significant model improvements were achieved by accounting for reduced heat flow into the solid bed due to the porous surface structure in the solid conveying zone, along with a new assumption for the flow temperature at the phase boundary between the solid bed and melt film.

Integrating Deep Learning with Generative Design and Topology Optimization for Efficient Additive Manufacturing

Abstract. Additive manufacturing (AM) through generative design and topology optimisation creates complex, lightweight structures with exceptional material efficiency and structural integrity. When coupled with deep learning functionality, generative design and topology optimisation can explore broader design spaces and optimise more efficiently, creating novel AM structures that utilise material more efficiently and have better strength and performance than their counterparts created through conventional AM methods. The study tackles how deep learning models such as convolutional neural networks (CNNs) can be integrated into generative design and topology optimisation and how these integration help optimise material usage, production time and performance. Case studies from the aerospace, automotive, and healthcare industries exemplify how these synergies resulted in more resilient, cost-effective designs that would not have been possible through conventional AM approaches. The study focuses on material usage efficiency, reduction in production time and performance improvement to showcase how deep learning integrations enhance the process from design conceptualisation, through iterations, to final production.

Optimizing Power Density in Partially Coated Cantilever Beam Energy Harvesters: A Cost-Effective Design Strategy

Optimizing Power Density in Partially Coated Cantilever Beam Energy Harvesters: A Cost-Effective Design Strategy

Effects of transverse loading on the ultimate strength prediction of stiffened panels under biaxial loads: Potential improvements to the IACS rule formulation

The current International Association of Classification Societies (IACS) rule for designing stiffened panels was found in Wang et al. (2024) to conservatively predict the ultimate strength of panels when transverse loads predominate. This conservatism arises from the overestimation of bending moments acting on stiffeners by directly applying the beam analogy in both longitudinal and transverse directions in the rule formulation when evaluating stiffener yielding.To address this issue, this paper applies the orthotropic plate theory to calculate bending moments experienced by the stiffeners of panels under biaxial loads. Orthotropic properties are derived from equivalent sectional areas and moments of inertia. The predicted bending moments are validated through comparisons with numerical simulations. The effects of boundary conditions and deflection patterns with varying numbers of half-waves are discussed. Based on the analytical results, a modification of the IACS rule formulation is proposed by introducing a correction factor to account for transverse loading effects in the bending moment calculations. The factor is a function of the ratio between longitudinal and transverse loading.The modified IACS rule formulation is verified through numerical simulations of aluminium panels using ABAQUS and comparisons with results from existing literature on steel stiffened panels under various biaxial loading conditions. The modified rule formulation shows improved accuracy in predicting the ultimate strength of stiffened panels, particularly in cases with dominating transverse loads. The modified IACS rule formulation can be useful for more reliable and cost-effective design of ships and offshore structures.

Low-power and cost-effective readout circuit design for compact semiconductor gas sensor systems

This study introduces a novel readout circuit architecture that enhances semiconductor gas sensor systems by reducing power consumption, enabling miniaturization, and improving economic viability. Validated at the PCB level, the design shows strong commercial potential by addressing power efficiency and signal accuracy challenges. The technology is adaptable for applications in environmental monitoring, industrial safety, and medical diagnostics, where efficient and reliable gas sensing is essential.

Cold solar: PVT heat exchanger designs for heat pump integration

There has been an increase in solar photovoltaic/thermal (PVT) research in recent years, however, relatively little research has been dedicated to the design of PVT collectors as part of a heat pump system. This study aims to identify cost-effective design strategies for a PVT collector absorber to be integrated into a ground source heat pump (GSHP) circuit and enhance heat capture from the ambient air. The effect of geometry, material selection, fins, and forced convection on the overall U-value and thermal performance coefficients of the collector, are evaluated under steady state conditions using numerical modelling tool COMSOL Multiphysics. An annual mean fluid temperature profile is derived from a PVT + GSHP system simulation to calculate the annual thermal energy output, energy-to-mass and energy-to-cost ratios of the absorbers. Results show that the addition of fins and forced convection have the greatest influence on collector thermal performance, while material selection has a negligible impact. The corrugated, polycarbonate absorber with 10 mm fins, generates 55 % more thermal energy (1,464kWhth/m2-yr) than the reference metallic sheet and tube collector at an energy-to-cost ratio 1/10th the reference, suggesting good market potential. An exergy analysis reveals that thermal exergy contributes 20 % to 50 % of the total exergy output, highlighting that low-temperature PVT designs exhibiting a smaller thermal share relative to electrical exergy compared to their higher temperature counterparts. This work’s novelty and contribution comes from PVT design specifically for GSHP integration, examined at component and system levels, from both technical and economic perspectives.

Post fire flexural behavior of mild steel based cold-formed built-up beams exposed to elevated temperature

The use of back-to-back built-up channel beams in cold-formed steel (CFS) structures is steadily rising. The growing demand for CFS sections as a cost-effective design solution has driven the development of these CFS built-up sections. Despite this, there has been limited research on the performance of mild steel (MS) based CFS at high temperatures, particularly regarding its flexural behavior. This study thoroughly explores the behavior of MS-based CFS beams with different spans under high temperatures, followed by cooling with air or water. It assesses the impact of thermal loading and evaluates the effectiveness of these cooling methods. Experimental findings are validated and analyzed in conjunction with Finite Element Modeling (FEM) using ABAQUS and the Direct Strength Method (DSM). The study also conducts a parametric analysis to determine how the varying span that affects flexural capacity of beam. Among beams heated to the same temperature, those cooled with water exhibit slightly lower load capacities than those cooled with air. The maximum load observed is 91.21 kN for the reference specimen, while the minimum load is 39.82 kN for the specimen heated for 90 min and cooled with water, resulting in a 78.45% difference between these values. Additionally, as heating duration increases, ductility of beam also increases. Various failure modes are observed based on different heating and cooling conditions across different beam spans. This study offers valuable insights into the performance of MS-based CFS beams under thermal stress and different cooling conditions, providing important data for structural design and safety in construction.

A computational strategy to improve the activity of tyrosine phenol-lyase for the synthesis of L-DOPA

Enzymes with high catalytic activity and stability are essential for industrial production, yet most natural enzymes do not meet these requirements. Therefore, efficient strategies for enzyme engineering are crucial. In this study, we developed a cost-effective computational design strategy to enhance the activity of tyrosine phenol-lyase (TPL) for the production of L-DOPA. By integrating structural analysis with computational design, and guided by our understanding of conformational flexibility of TPL, we identified a region where enhanced stability is most likely to facilitate enzyme activity. We screened stabilizing mutations by Cartesian_ddg in Rosetta. After identifying single stabilizing mutations, we grouped the nearby positions harboring multiple stabilizing mutations and calculated the energy of combinatorial variants. We found two promising groups where most variants exhibited lower calculated energy than the wild-type. Experimental validation showed five variants in these groups exhibit increased activity, with the two best variants showing catalytic activity enhancements of 1.8-fold and 1.6-fold compared to the wild-type enzyme.

Exploring the efficiency of employing Fe3O4-MWCNT Nanofluids in a heat sink equipped with circular micro pin-fins

This work investigates the effects of adding different turbulence-inducing elements and varying the concentration of Fe3O4-MWCNT hybrid nanofluid to evaluate the efficiency of a micro pin-fin heat sink. To achieve this objective, a multiphase Lagrangian-Eulerian method that includes gravity, thermophoresis, drag force, Saffman lift, virtual mass, and pressure gradient-induced force to model will employ hybrid nanofluids. The evaluation of heat sink efficiency includes the analysis of quantitative variables like surface Nusselt number, average Nusselt number, and the logarithmic mean temperature difference. Furthermore, a qualitative representation of flow and thermal distributions is illustrated by visualizing flow streamlines, vortex contours, and thermal contours. This topic is addressed in the current work by using the finite volume approach with Ansys Fluent 18.1. Using the multiphase Lagrangian-Eulerian approach, the hydrothermal performance of the Fe3O4-MWCNT hybrid nanofluid in a pin-fin heat sink is investigated. This article's novelty lies in its utilization of four distinct turbulator models, each with unique geometries and widths. These models are positioned within a heat sink with micro fins and are tested in the presence of Fe3O4-MWCNT nanofluids. According to the findings, using the hybrid nanofluid at a concentration of 5 % rather than 1 % causes an average Nusselt number rise of 7.3 %, 9.4 %, and 12.5 % in various heat sink segments. This study's most significant thermal enhancement is associated with case D, which demonstrated a 7 % improvement over the baseline scenario by employing Fe3O4-MWCNT at a concentration of 5 % and a Reynolds number of 2400. It has been demonstrated that hybrid nanofluids have thermal efficiency between 600 and 2400 Reynolds numbers. The thermal efficiency criteria represent the base model, denoted by η = 1. A higher thermal efficiency denotes a more cost-effective design that offers superior heat transmission at a reduced pressure drop. It has been discovered that raising the concentration of hybrid nanofluids improves the micro pin fin heat sink's thermal performance by increasing the heat transfer coefficient.

Implementation of Solar PV Protection System in Indonesia: A Review

Conventional energy sources will run out if used continuously and damage the environment. Therefore, it is necessary to develop other energy sources that are safe, environmentally friendly, and inexhaustible known as renewable energy sources to meet energy needs in Indonesia. This article presents a review that discusses the protection of solar panels and PLTS. Solar panels are vulnerable to lightning strikes and other electrical disturbances, so an effective protection system is needed. This study uses a qualitative method through a literature study, reviewing various protection methods such as conventional and electrostatic lightning rods, good grounding systems, and overcurrent detection devices such as Solar Charge Controller (SCC) and Maximum Power Point Tracking (MPPT). In addition, battery protection with Automatic Transfer Switch (ATS) and Low Voltage Disconnected (LVD) is also discussed. Using Arduino Uno, ESP 32, and PLC, automation approaches offer real-time monitoring and control solutions for solar power plant performance. Innovations in the lightning protection zone concept and minimal quantity measurement schemes enable more cost-effective design of protection systems without reducing the level of protection. The results show that these various protection methods can provide effective and efficient protection for solar power plants, enabling optimization of system function and safety. In conclusion, the protection systems reviewed in this study offer a sustainable solution to Indonesia's energy challenges by utilizing the maximum potential of solar energy. The potential for further research is presented in this article to develop more efficient and effective protection methods.

Blast wave ingress into a room through an opening – Review of past research and US DoD UFC 3-340-02

Blast wave ingress into a room through a facade opening results in complex pressure-time loadings on interior surfaces due to shock diffraction and interior reflections. The U.S. DoD UFC 3-340-02 Structures to Resist the Effects of Accidental Explosions includes a method to predict internal loading for such cases. Parameters such as the opening size, room dimensions and the external pressure wave characteristics influence the interior loading. Recent work suggests that the UFC methodology might overpredict the interior loading by some 600%. Such conservatism can result in over-engineered or prohibitively expensive protective solutions. In this paper we critically review the methodology of the UFC, that of Kaplan’s preceding work (on which the UFC relies), and the experimental data that informed both these works. Through a series of 45 case-studies we compare the UFC and Kaplan’s predictions with those of a computational fluid dynamics (CFD) model. The UFC consistently overpredicts the CFD area-averaged peak pressure of the back wall by up to 290% and the side-wall by up to 425%. Similarly, the UFC overpredicted the CFD side wall positive phase impulse by up to 565%. By contrast, the UFC predicted back wall positive phase impulse was similar to the CFD results. As our CFD results for side and back walls are area averaged, and not solely for the wall centre-point, as in other recent work, our paper gives support for the use of CFD prediction over the UFC for cost-effective design of structures to resist blast ingress.

Improving current-matching in textured perovskite/silicon tandem solar cells via a thickness control strategy

This study presents an analysis of a two-terminal tandem solar cell that integrates metal-doped, lead-free double Cs2AgBi0.75Sb0.25Br6 perovskite with silicon to enhance overall energy conversion efficiency. This study explores how the thicknesses of the top and bottom sub-cells affect current-matching in two-terminal tandem perovskite/silicon solar cells with two separate planar and textured configurations. Using numerical modeling in MATLAB, and considering dominant recombination effects, we calculated the performance parameters of the device. We investigated the optical and electrical properties of textured tandem structures, focusing on current- matching and the influence of layer thickness on device performance. Given the complexity, time, and expense involved in constructing tandem solar cells, being able to analytically determine the thickness at which current-matching occurs can be highly advantageous. This approach offers the benefit of providing a precise analytical relationship for this purpose. Our findings demonstrate that increasing the top cell thickness enhances current density and power conversion efficiency, but at the cost of the bottom cell’s efficiency due to increased light absorption. Moreover, we discovered a nearly linear behavior between the thickness of the top and bottom cells for achieving current-matching. The study highlights the critical balance required to optimize layer thicknesses, thereby improving the design and performance of tandem solar cells. These insights are significant as they pave the way for more efficient and cost-effective tandem solar cell designs in the future, potentially accelerating the adoption of advanced photovoltaic technologies. The results show good agreement with experimental data, validating our model.