Critical Design Factors Research Articles

Improving the Mental Health of Surgical Teams Through Operating Room Design.

In this study, we aim to develop and propose an evaluation method for analyzing the design of operating rooms (ORs) from the perspective of surgical teams' reported experiences and stress levels. Stress and burnout of surgical team members can lead to diminished performance and medical errors, which endangers the safety of both the patients and team members. The design and layout of the OR play a critical role in managing such stress. To understand surgical teams' spatial needs related to their experiences and stress, we administered a survey and in-depth focus group discussions to three surgical teams from the same organization. The identified spatial needs were translated into functional scenarios and spatial metrics, essentially viewing the OR through the perspective of users. Our analysis revealed four integral sections-patient flow, room organization, access to facilities/medical equipment/support staff/team members, and staff well-being-identified as critical design factors associated with the experiences and stress levels of the surgical teams in the ORs. We expect this method to serve as a tool for evaluating the effect of the design of OR layouts on stress, thereby supporting the well-being and resiliency of surgical teams.

Transient heat transfer simulation, sensitivity analysis, and design optimization of shallow ground heat exchangers with hollow-finned structures for enhanced performance of ground-coupled heat pumps

Ground-Coupled Heat Pumps (GCHPs) are regarded as an effective technology for building energy development and residential hot water production. The essential challenges to encompass these systems in urbanized areas are the highly drilling and initial costs of GCHPs. To overcome this challenge, researchers and industries are seeking innovative solutions by focusing on optimizing the structure of ground heat exchangers (GHXs), which act as the essential component for efficient geothermal energy extraction in GCHPs. Hence, this paper introduces a comprehensive comparative numerical investigation of an innovative U-tube GHX with a hollow-finned structure for augmenting the performance of the GCHPs. This design remarkably enhances the thermal performances, reduces the thermal resistance, therefore minimizes borehole depth, reduces drilling costs, boosts GCHP's financial viability, and bolsters geothermal energy utilization. Therefore, a series of three-dimensional analyses of transient heat extraction is executed and validated using a practical field experiment performed by the authors' research group to investigate the thermal behavior of the hollow-finned U-tube GHX at different fin configurations and compare its efficacy to typical circular U-tube GHX. More so, a parametric study and sensitivity analysis are also performed to identify the influence of critical operational and design factors on the heat extraction of the proposed hollow-finned U-tube GHX compared to the typical circular GHX. The influences of groundwater flow on the transient heat extraction were also examined. Additionally, a dimensionless shape factor is introduced to assess the implications of the U-tube geometry with hollow-finned on the thermal performance of the GHXs. Furthermore, design optimization was also conducted by examining different branched-shaped hollow-fin's U-tube GHX configurations. The findings indicate that the mean heat transfer rate of hollow-finned U-tube GHX can be increased by 44.58 % compared to the conventional circular U-tube GHX. Correspondingly, the total thermal resistance of hollow-finned U-tubes GHX was reduced by 47.71 %. It also identified that the Y-shaped hollow-finned U-tube GHX was the optimal design among the investigated configurations of branched-shaped hollow-finned U-tube GHXs, demonstrating an increase of 52.64 % compared to the conventional circular U-tube GHX. Moreover, it is revealed that a lower shape factor enhances the heat transfer rate significantly. Furthermore, the optimal mass flow rate and desired number of hollow-finned were estimated as 0.80 kg/s and six fins, respectively. Conclusively, this investigation concludes that the hollow-finned U-tube GHX can greatly enhance the heat extraction rates and reduce borehole thermal resistance, which can increase the efficiency of GCHP systems.

Numerical Study of Effects of Inhomogeneous Roughness on the Ship Friction Resistance

The cleanliness of a ship hull is crucial for energy saving. Biofouling, which can cause microbiological corrosion, can also increase ship resistance. If left unchecked, this can lead to inefficient energy use and increased emissions, contributing to global warming. Ship resistance is a critical factor in ship design, which affects ship powering. The analysis of friction resistance due to biofouling on a ship hull requires an examination of the distribution of roughness height (ks), which is randomly distributed. In this study, an analysis of friction resistance coefficient (CF) due to inhomogeneous roughness is carried out with the help of CFD simulations with a full-scale model at 19 kn and 24 kn. The roughness of three ship segments, namely aft-hull, midship, and fore-hull, varies with ks values of 125 μm (P), 269 μm (Q), and 425 μm (R), respectively, while maintaining the same wetted surface area (S) in each segment. According to the simulation results, the RQP model produces the highest CF of 2.154 x 10-3, while the PQR model produces the smallest CF of 2.119 x 10-3 each at speed 24 knots. The CF contributes an average of 72.2% CT.

Towards bridging thermo/electrocatalytic CO oxidation: from nanoparticles to single atoms.

Proton exchange membrane fuel cells (PEMFCs), as a feasible alternative to replace the traditional fossil fuel-based energy converter, contribute significantly to the global sustainability agenda. At the PEMFC anode, given the high exchange current density, Pt/C is deemed the catalyst-of-choice to ensure that the hydrogen oxidation reaction (HOR) occurs at a sufficiently fast pace. The high performance of Pt/C, however, can only be achieved under the premise that high purity hydrogen is used. For instance, in the presence of trace level carbon monoxide, a typical contaminant during H2 production, Pt is severely deactivated by CO surface blockage. Addressing the poisoning issue necessitates for either developing anti-poisoning electrocatalysts or using pre-purified H2 obtained via a thermo-catalysis route. In other words, the CO poisoning issue can be addressed by either thermal-catalysis from the H2 supply side or electrocatalysis at the user side, respectively. In spite of the distinction between thermo-catalysis and electro-catalysis, there are high similarities between the two routes. Essentially, a reduction in the kinetic barrier for the combination of CO to oxygen containing intermediates is required in both techniques. Therefore, bridging electrocatalysis and thermocatalysis might offer new insight into the development of cutting edge catalysts to solve the poisoning issue, which, however, stands as an underexplored frontier in catalysis science. This review provides a critical appraisal of the recent advancements in preferential CO oxidation (CO-PROX) thermocatalysts and anti-poisoning HOR electrocatalysts, aiming to bridge the gap in cognition between the two routes. First, we discuss the differences in thermal/electrocatalysis, CO oxidation mechanisms, and anti-CO poisoning strategies. Second, we comprehensively summarize the progress of supported and unsupported CO-tolerant catalysts based on the timeline of development (nanoparticles to clusters to single atoms), focusing on metal-support interactions and interface reactivity. Third, we elucidate the stability issue and theoretical understanding of CO-tolerant electrocatalysts, which are critical factors for the rational design of high-performance catalysts. Finally, we underscore the imminent challenges in bridging thermal/electrocatalytic CO oxidation, with theory, materials, and the mechanism as the three main weapons to gain a more in-depth understanding. We anticipate that this review will contribute to the cognition of both thermocatalysis and electrocatalysis.

Bond strength prediction of FRP bars to seawater sea sand concrete based on ensemble learning models

The bond strength between fiber-reinforced polymer (FRP) bars and seawater sea sand concrete (SWSSC) is a critical factor in structural design and applications. To address the inherent nonlinear problem, where bond strength is closely tied to constitutes of concrete and properties of FRP bar, this paper presented a novel approach to predict the bond strength using ensemble learning models and investigated the effects of input parameters on bond strength. For this purpose, a dataset of tests of pullout failures was determined consisting of 13 input parameters. Based on the determined dataset, two prediction models were developed using ensemble learning algorithms Random Forest (RF) and XGBoost. Simultaneously, a bond strength equation for pullout failures was derived from the ACI 440.1R-15 database since the existing equation in the code was originally developed to address splitting failures. The developed models demonstrated commendable accuracy based on statistical evaluations. Given its superior prediction and comparable generalization performances compared to the XGBoost model, the RF model was chosen for bond strength prediction compared to the developed equation. Comparative results favored the RF model, which significantly outperformed the developed equation in bond strength prediction. Furthermore, the study investigated the effects of input parameters by analyzing SHAP (SHapley Additive exPlanations) values. The analysis unveiled the influential mechanisms of mechanical property and composition of SWSSC, along with the mechanical, geometric, and surface properties of FRP bar on bond strength. In conclusion, the developed models represent an effective approach for predicting the bond strength of pullout failures between FRP bars and SWSSC.

Controlled Surface Functionalization Using Aryldiazonium Salts for the Development of Aptasensing Platforms

It is well known that both the aptamer surface density and surface chemistry can have a strong influence on the analytical performance of aptasensors based on target-induced conformational changes1. In this context, we report here an improved protocol for obtaining aptasensing platforms which allows fine-tuning the DNA aptamer surface coverage. First, glassy carbon substrates were functionalized with ethynylphenyl groups through the electrochemical reduction of silyl-protected ethynylphenyl diazonium tetrafluoroborates followed by deprotection with tetrabutylammonium fluoride2. The successful removal of the protecting groups (triisopropylsilyl-, triphenylsilyl- and tris(biphen-4-yl)silyl-) was confirmed by X-ray photoelectron spectroscopy and cyclic voltammetry in the presence of Fe(CN)6 3-/4- as soluble redox probe. Following “click” post-modification with suitable derivatization reagents, the surface coverage with ethynylphenyl groups was assessed using complementary techniques such as XPS, cyclic voltammetry and chronocoulometry. For example, the F/C surface ratio of substrates derivatized with 1-(2,2,2-trifluoroethoxy)-6-azidohexane provided an indication of the functionalization degree, and the integration of Fc/Fc+ voltammetric peaks for substrates modified with N-(6-azidohexyl)ferrocenecarboxamide allowed a quantitative determination of the surface coverage. Both techniques showed a good correlation between the protective group size and the surface coverage with alkyne groups. Likewise, we observed a similar trend for substrates derivatized with azide-modified oligonucleotides, where the surface packing density was determined based on the chronocoulometric response of Ru(NH3)6 3+, a cationic redox probe which binds with the negatively charged phosphate groups from the oligonucleotide backbone. As proof of concept, we further developed an electrochemical molecular beacon aptasensor employing a ferrocene-labeled quinine aptamer. We demonstrate that the aptamer surface density, and ultimately the analytical performance of molecular beacon aptasensors, can be effectively fine-tuned by employing silyl protecting groups of different sizes.Acknowledgements This work was supported by a grant from the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number PN-III-P4-ID-PCE-2020-2474, within PNCDI III. References Onaş, A. M., Dascălu, C., Raicopol, M. D. & Pilan, L. Critical Design Factors for Electrochemical Aptasensors Based on Target-Induced Conformational Changes: The Case of Small-Molecule Targets. Biosensors 12, (2022).Leroux, Y. R., Fei, H., Noël, J.-M. M., Roux, C. & Hapiot, P. Efficient covalent modification of a carbon surface: Use of a silyl protecting group to form an active monolayer. J. Am. Chem. Soc. 132, 14039–14041 (2010).

Hierarchical Deployment of Vortex Generators for Wake Management in Finned-Tube Heat Exchanger

While developing thermal management systems, volumetric compactness of the heat exchange module is a critical design factor. This three-dimensional computational analysis seeks to boost the thermal compactness of fin-and-tube heat exchangers by employing winglet-type vortex generators. Due to the fact that the thermo-hydraulic performance of vortex generators in such thermal systems is determined by three distinct design parameters, namely the attack angle, spatial location, and geometric aspect ratio, a concurrent parametric analysis of all three design parameters is conducted to gain a thorough understanding. In addition, regression analysis is applied to develop functional correlations that can predict the enhanced thermo-hydraulic performance of the heat exchangers. The improvements in wake-affected heat transfer brought on by the modifications are also specifically explored, along with other aspects of the augmentation mechanism. The highest thermal augmentation over the wake-affected fin is seen as 120%. Based on a thermo-hydraulic tradeoff, the friction factor increases exponentially with the attack angle, and the rate of increase is lowest for 15–30 degree range of attack angle and highest for 45–60 degree range. Certainly, there are multiple locations where winglets can be erected, and heat transfer enhancement by each potential location incurs linearized increase in the friction factor.

Challenges for the Design of International Assessments: Sampling, Measurement, and Causality

This paper examines critical design factors that influence data quality in educational research, using international large-scale educational assessments as an example. We will focus on statistical challenges related to sampling, measurement, and causality. While international assessments employ rigorous random sampling techniques, deviations such as exclusions and non-participation can introduce bias and affect representativeness. In terms of measurement, although these assessments excel in core domains, there is a growing call for broader assessment areas, such as environmental literacy and civic education. Additionally, concerns are emerging about the quality of context surveys. Causality remains a central concern, and despite the challenges posed by the cross-sectional design, combining data and applying sophisticated analytical methods can help address causal questions. Recognising the interconnectedness of sampling, measurement, and causality is essential for conducting robust research and informing evidence-based policies and practices.

Integrating Aggregation Induced Emission and Twisted Intramolecular Charge Transfer via Molecular Engineering

AbstractThe pursuit of sensitive fluorescent chromophores with integrated aggregation‐induced emission (AIE) and twisted intramolecular charge transfer (TICT) properties are attractive due to the tunable emission properties and increased intensity. However, this type of chromophore has yet to be exemplified mechanistically. In this study, a strategy is presented for manipulating the formation of TICT and the AIE effect through molecular engineering. The feasibility of TICT properties is validated by theoretical calculations and ultrafast spectroscopies. By precisely adjusting the hydrophobicity of the donor group, the fluorescence is significantly enhanced through the addition of poor solvent. These findings not only provide mechanistic elucidation for chromophores exhibiting integrated TICT and AIE properties in various environmental conditions but also underscore the critical factors for the systematic design of chromophores with high tunability and strong emissions.

A Review of EMI Research of High Power Density Motor Drive Systems for Electric Actuator

With the global attention given to energy issues, the electrification of aviation and the development of more electric aircraft (MEA) have become important trends in the modern aviation industry. The electric actuator plays multiple roles in aircraft such as flight control, making it a crucial technology for MEA. Given the limited space available inside an aircraft, the power density of electric actuators has become a critical design factor. However, the pursuit of high power density results in the need for larger rated power and higher switching frequency, which can lead to severe electromagnetic interference (EMI) issues. This, in turn, poses significant challenges to the overall reliability of the electric actuator. This paper provides a comprehensive review of EMI in high power density motor drive systems for electric actuator systems. Firstly, the state of the art of electric actuator systems are surveyed, pointing out the contradictory relationship between high power density and EMI. Subsequently, various EMI modeling approaches of motor control systems are reviewed. Additionally, the main EMI suppression methods are summarized. Active EMI mitigation methods are emphasized in this paper due to their advantages of higher power density compared with passive EMI filters. Finally, the paper concludes by summarizing the EMI research in motor drive systems and offering the prospects of electric actuators.

Reconstruction of narrowband solar radiation for enhanced spectral selectivity in building-integrated solar energy simulations

Solar radiation is a critical factor in advanced envelope design and solar energy's building integration, necessitating a shift from broadband solar radiation analyses towards more precise narrowband or spectrum-focused approaches. Understanding the performance potential of spectral-selective materials or structures requires accurate solar spectral information at specified locations, a feature often overlooked by conventional modeling tools. This work presents an innovative solar decomposing model capable of differentiating key solar irradiation components—visible and infrared—from broadband solar irradiance, without the need for expensive spectrum measurements. Our approach employs the extreme boosting regression tree method and leverages existing or easily derivable data from typical weather files. An exploratory analysis of the importance and interaction of different features in predicting solar irradiation components is also conducted. The results show that the proposed algorithm has an R2 of 0.981 and 0.990, RMSE of 18.280 and 18.390, and MAE of 7.989 and 8.011, for predicting VIS and NIR amount in DNI, respectively (for the strongest model using all the predictors within the dataset). This research offers an added layer of practicality by including case studies demonstrating how the solar decomposition models serve in real-world applications, especially in the integration of wavelength-selective devices like window systems and transparent solar cells into advanced envelope designs. Such real-world testing has verified the presence of a disparity between the power output calculation of NIR-selective transparent photovoltaics upon the broadband solar radiation data and the suggested narrowband solar radiation data, potentially resulting in a maximum deviation of 15.7 %. The decomposing models developed empower researchers and designers to generate new weather files comprising narrowband solar irradiance data, thereby enhancing their capacity to examine the influence of spectral-selective materials on a building's solar performance using existing solar simulation programs. The proposed method will be further improved by including more data from different climate zones and weather characteristics in the training model and validating through field measurements.

An approach for the material selection and use in industrial-energy facilities

The place and characteristics of architectural structures in the developing production, industry and energy fields are important at the point of architecture being a versatile and interdisciplinary practice. Industrial-energy facilities are buildings that are mostly established in areas outside the city and designed to be protected against environmental factors, where energy and industrial activities are carried out. Since it is a production-oriented system, it includes many different operational processes. These buildings are used for a wide range of purposes such as manufacturing, storage, and distribution. The design of an industrial building plays an important role in determining the productivity, efficiency and safety of the facility. In this view, material selection has been evaluated as a critical factor in architectural design of industrial-energy facilities. It affects the environmental sustainability, structural performance, and aesthetic appeal of the built environment. The materials used in the construction of an industrial building should also be carefully selected. These buildings experience heavy wear and tear, and therefore need to be durable and long-lasting. Steel and concrete are popular materials because of their strength and durability, while also being flexible in accommodating the changing needs of the business. This paper presents a scientific approach to material selection that considers sustainability, performance, and aesthetics criteria. Studies on the structure and other characteristics of industrial-energy facilities, which constitute the main problematic of the study, has been examined, and it has been aimed to reveal the theory and knowledge at the point of the experience of the authors. In this context, the aim of the study is to reveal the architectural features, commonly used materials and material selection criteria of industrial-energy facilities by determining them through theoretical knowledge, analysis, observation and professional experience.

Omega and CTOA for dynamic steady-state fracture propagation and their dependency to fracture speed

Dynamic ductile fracture in pressure vessels is an increasingly important topic. Recent catastrophic pressurised pipeline failures highlighted the critical needs of reliable pipeline infrastructures. The ability for line pipe steels to resist fracture is a critical design factor for governing the severity level of fracture failures given that it determines if fracture propagates for several kilometres or is arrested quickly. Developing a reliable fracture toughness test to systematically evaluate new steel products’ quality is therefore important. In the current work, a novel small-scale fracture toughness parameter Omega was implemented and compared to the well-established parameter CTOA, with respect to their performance of characterizing steady-state fracture propagation and their dependencies to Fracture Speed. The current experimental data were collected from a 3-point bend dynamic Drop Weight Tear Test (DWTT) for 9 line pipe steels with different thicknesses and impact conditions. It was found that the Omega gives significantly better description for steady-state fracture propagation; and it is found to be independent of the Fracture Speed. The current study confirmed that in DWTT, CTOA values decrease with increasing Fracture Speed. Finally, a simple analytical model is proposed to describe this dependency (CTOA-Fracture Speed) from a geometrical standpoint.

Assessment of Na-Ion Battery Performance Using Machine Learning

In the last couple of decades, the smart design of battery electroactive materials and cells to satisfy the demand for efficient energy storage has attracted significant research interest. Li-ion batteries have been widely employed in hybrid cars, power plants, and electronic devices. However, sodium-ion batteries are getting increasing attention as sodium is much more earth-abundant and inexpensive than lithium. In this work, we studied the impact of critical materials and cell design factors, electrode preparation methods, and operational descriptors on the discharge capacity and the cycle life of the Na-ion batteries using machine learning. The dataset was created from 355 experimental papers published in 2015-2020 and contained 1227 different experiments: 747 and 380 cases had only the anode and the cathode studies, respectively, whereas 100 cases were for the full cells. In the analysis, 38 descriptors were used on the electrode materials, electrolyte, and electrode structure, in addition to material synthesis and electrode preparation methods. On the other hand, peak discharge capacity and cycle life (the highest cycle number at which 80% of the peak capacity is retained) were selected as the target (output) variables. Random forest, gradient boosting, support vector machines (for regression), and decision tree (for classification) methods were used for the analysis. In the analyses, the dataset was randomly divided into two subsets: 75% to build the models (training and validation) and 25% to test the performance of the models in predicting the unseen data. Five-fold cross-validation was applied for hyperparameter optimization. Root mean square error (RMSE) was calculated as the performance indicator.The pre-analysis of the dataset presented that the highest average discharge capacity is obtained with the alloy-based anodes, followed by metal sulfides. However, their average cycle life is relatively low. In contrast, carbon-based anodes present prolonged cycle life even though they have low discharge capacities. Moreover, full-cell applications that couple the alloy-based anodes with the metal oxide cathodes show the highest average discharge capacity. Lastly, for anode or cathode half-cell studies, using a single solvent leads to higher discharge capacities and cycle life. In contrast, mixed solvents perform better in full cells.Random forest models successfully predicted the discharge capacity and demonstrated the relative significance of descriptors (Figure 1). Boruta analysis, performed for feature importance, showed that the anode and cathode types are highly effective. At the same time, the synthesis method and crystal structure were also found to be influential. On the other hand, we used classification models, which can be considered as range prediction instead of point prediction, instead of regression models to analyze the cycle life data. Decision tree classification of cycle life was quite effective, leading to heuristic rules for selecting the anode and cathode materials or methods for synthesis and electrode preparation. Material synthesis conditions are essential for high cycle life for the anode, while solvent selection is also critical for the cathode studies. Figure 1. Random Forest Regression model for the prediction of the peak discharge capacity for a) anode training, b) anode testing, c) cathode training, and d) cathode testing sets

Full-field deformation and failure analysis for compression after impact of carbon fibre reinforced polymer laminates

Residual compressive strength after impact is a critical design factor in assessing damage tolerance of carbon fibre-reinforced polymers (CFRP) for structural applications in aircraft. This study investigated compression after impact (CAI) performance of quasi-isotropic CFRP laminates by measuring 3D deformation and strain using three-dimensional digital image correlation (3D DIC). Before the CAI, these test panels were subjected to drop-weight impact testing with energy levels representing visible impact damage (VID). During the CAI testing, deformation behaviours throughout the full loading sequence were captured by twin-camera imaging systems at the front and back faces of panels at standard speed. A single-camera high-speed imaging system captured ultimate failure behaviours at the sample front face. The single-camera high-speed system used four planar mirrors to achieve 3D DIC measurements. This study investigated the effect of boundary conditions on the compressive behaviours of the test panels, where the effect of additional support plates at the front and back surfaces to reduce the unsupported area was compared with the boundary condition of standard anti-buckling guides. The panels with added supports were found to experience deformations dominated by local buckling and final out-of-plane displacements in an S-shaped profile. These panels also exhibited residual strength reductions correlating to impact damage levels and ultimate failure initiating at the damaged region and propagating rapidly along the transverse axis. In comparison, the panels without added supports exhibited failure dominated by global buckling as manifested by large out-of-plane displacements, which had an arc-shaped profile. The DIC measurements were compared against those of mounted biaxial strain gauges. The single-camera high-speed system was shown not only to be feasible for high strain rate testing applications; it also offered a significant cost saving compared to an equivalent twin-camera high-speed system.

Study on Resonance Phenomenon Caused by Voltage Fluctuation of Power Supply in JT-60SA EF Coil

For the large research Tokamak JT-60SA, evaluating the withstand voltage between conductors is one of the most critical factors for the coil design. The power supply feeding the coil injects a wide spectrum of frequency components. The transient response and resonance phenomena induce a non-uniform voltage distribution in the coil. The transiently concentrated voltage can cause the insulation breakdown between conductors, and JT-60SA may not be able to operate safely. This study conducted an impulse test to evaluate the withstand voltage between adjacent conductors for an equilibrium field (EF) coil. The actual power supply voltage for the EF coil was measured to investigate the ramp rate (dv/dt) and frequency spectrum. In addition, based on the results of a resonance test of the EF dummy coil, a circuit simulation model for the EF coil was developed to evaluate the effect of the transient response and resonance phenomenon on the voltage in the coil. The results of this study provide fundamental data that can be used to ensure that the EF coil does not cause insulation breakdown.

ECKN: An Integrated Approach for Position Estimation, Packet Routing, and Sleep Scheduling in Wireless Sensor Networks.

Network lifetime and localization are critical design factors for a number of wireless sensor network (WSN) applications. These networks may be randomly deployed and left unattended for prolonged periods of time. This means that node localization is performed after network deployment, and there is a need to develop mechanisms to extend the network lifetime since sensor nodes are usually constrained battery-powered devices, and replacing them can be costly or sometimes impossible, e.g., in hostile environments. To this end, this work proposes the energy-aware connected k-neighborhood (ECKN): a joint position estimation, packet routing, and sleep scheduling mechanism. To the best of our knowledge, there is a lack of such integrated solutions to WSNs. The proposed localization algorithm performs trilateration using the positions of a mobile sink and already-localized neighbor nodes in order to estimate the positions of sensor nodes. A routing protocol is also introduced, and it is based on the well-known greedy geographic forwarding (GGF). Similarly to GGF, the proposed protocol takes into consideration the positions of neighbors to decide the best forwarding node. However, it also considers node residual energy in order to guarantee the forwarding node will deliver the packet. A sleep scheduler is also introduced in order to extend the network lifetime. It is based on the connected k-neighborhood (CKN), which aids in the decision of which nodes switch to sleep mode while keeping the network connected. An extensive set of performance evaluation experiments was conducted and results show that ECKN not only extends the network lifetime and localizes nodes, but it does so while sustaining the acceptable packet delivery ratio and reducing network overhead.

Investigation of the Shear Behavior of Concrete Beams Reinforced with FRP Rebars and Stirrups Using ANN Hybridized with Genetic Algorithm.

The shear strength prediction of concrete beams reinforced with FRP rebars and stirrups is one of the most complicated issues in structural engineering applications. Numerous experimental and theoretical studies have been conducted to establish a relationship between the shear capacity and the design variables. However, existing semi-empirical models fail to deliver precise predictions due to the intricate nature of shear mechanisms. To provide a more accurate and reliable model, machine learning (ML) techniques are adopted to study the shear behavior of concrete beams reinforced with FRP rebars and stirrups. A database consisting of 120 tested specimens is compiled from the reported literature. An artificial neural network (ANN) and a combination of ANN with a genetic optimization algorithm (GA-ANN) are implemented for the development of an ML model. Through neural interpretation diagrams (NID), the critical design factors, i.e., beam width and effective depth, shear span-to-depth ratio, compressive strength of concrete, FRP longitudinal reinforcement ratio, FRP shear reinforcement ratio, and elastic modulus of FRP longitudinal reinforcement rebars and FRP stirrups, are identified and determined as input parameters of the models. The accuracy of the proposed models has been verified by comparing the model predictions with the available test results. The application of the GA-ANN model provides better statistical results (mean value Vexp/Vpre equal to 0.99, R2 of 0.91, and RMSE of 22.6 kN) and outperforms CSA S806-12 predictions by improving the R2 value by 18.2% and the RMSE value by 52.5%. Furthermore, special attention is paid to the coupling effects of design parameters on shear capacity, which has not been reasonably considered in the models in the literature and available design guidelines. Finally, an ML-regression equation considering the coupling effects is developed based on the data-driven regression analysis method. The analytical results revealed that the prediction agrees with the test results with reasonable accuracy, and the model can be effectively applied in the prediction of shear capacity of concrete beams reinforced with FRP bars and stirrups.

Stakeholder inclusion in the design and development of equipment for the modernizing mining sector in South Africa

A people-centric, systematic approach that involves different stakeholders is considered necessary to successfully address changes associated with modernizing the South African mining industry. In this paper we discuss the inclusion of various South African mining industry stakeholders, particularly the employees, in equipment design and development processes. Data was acquired through a literature review and inputs from South African mining industry stakeholders through focus group discussions, interviews, and an online survey. It was suggested that some of the areas that could be improved by the inclusion of employees in the process are design quality, ergonomics, equipment acceptance by the workforce, safety, efficiency, skills, insight into context of use, and early design iterations and identification of problems. Among the issues considered to be barriers to inclusion were lack of buy-in, lack of resources, difficulty in manufacturers accessing the mines, difficulties in involving too many people, intellectual property concerns, and unavailability of mine employees due to their key responsibilities. Identified critical factors in the equipment design and development process include iterative design, stakeholder participation throughout the process, needs analysis through consultation, and change management. A guideline was developed for worker inclusion in equipment design and development that could be used by the South African mining industry. The study identified several economic and social benefits of including stakeholders in the early stages of design and development. It is recommended that the South African mining industry considers using the developed guideline.

Benchmark and strategy development for microbial fuel cells in industrial wastewater treatment

The chemical energy hidden in wastewater can be extracted, turning an energy‐intensive treatment process into an energy‐independent one. However, conventional aerobic treat‐ ment is very energy intensive, and anaerobic treatment requires a post‐treatment step to meet stringent discharge requirements. Therefore, Microbial Fuel Cells (MFCs) have attracted a lot of attention because of their ability to extract electrical energy directly from wastewater during the treatment process. Since combustion losses can be avoided, theoretically the greatest energy value can be obtained from the organic load. However, most MFC research is currently still taking place on a laboratory scale in the treatment of synthetic or municipal wastewater. Commercialization of MFC technology will require large‐scale plants, for which a suitable MFC design and operation concepts must first be identified, since neither configuration nor operating system has been clearly established yet. In addition, no specific concepts and application fields currently exist for the treat‐ ment of industrial wastewater.Consequently, with regard to MFCs in industrial wastewater treatment, the aim of this work is to develop a benchmark that serves for modeling the required overall efficiency of MFCs and to identify the most relevant key factors in order to derive enhancement strate‐ gies. By providing an overview of current MFCs in industrial wastewater treatment and developing a benchmark, the targets for long‐term operation of MFCs can be established allowing critical factors for design and operation to be identified. The resulting enhance‐ ment strategies were validated and the overall evaluation with the developed benchmark allowed an assessment regarding the commercialization potential.Compared to the first MFC design (MFC 1.0), the enhanced MFC design (MFC 2.0) increased the power density by a factor of up to 11 and extended the long‐term stability to one year by increasing the specific cathode surface area and reducing the electrode spacing in conjunction with avoiding fiber clogging on the anode side. In addition to using beneficial brewery wastewater with high content of easily degradable organic acids and high conductivity, the performance of the MFC was further stabilized and improved by changing the operating mode to continuous operation and reducing the hydraulic re‐ tention time to 6 h, resulting in a mean organic removal rate of 6.5 ± 1.9 kg/(m3 · d). Although the overall energy efficiency is low compared to anaerobic treatment, the enor‐ mous wastewater treatment potential forms the basis for MFCs to become an alternative to conventional treatment technologies if self‐sufficient treatment is targeted. Due to the wide range of operating conditions and the modularity of stack systems, MFCs can become a promising option especially for industrial wastewater treatment.