System Capacity Research Articles

Impact of Slab Curling on Backcalculation Analysis

Falling Weight Deflectometer (FWD) testing is performed on rigid pavements to assess the in-situ structural capacity of the pavement system, to evaluate the load transfer efficiency across transverse joints/cracks and to identify joints with high possibility of voids underneath the slabs. Tests are performed at different times of the day (day and night), different seasons and different temperature conditions. This data is used in the analysis to identify the network needs and prioritize these needs considering budget and performance constraints. One key issue in this process is that FWD data collected under different environmental conditions is compared and decisions are made based on the comparison results. Therefore, an effort should be made to minimize the impact of the difference in environmental conditions during FWD testing on the final analysis results. Decisions, such as repair joints having low load transfer efficiency, underseal joints with voids, or repair slabs with low structural capacity, are made based on analysis of results of FWD testing that was performed under different temperature and moisture conditions. A classic example of temperature impact on Maintenance & Rehabilitation (M&R) decision is corner curling, which may be identified mistakenly as potential void. Undersealing the joint in this case may cause more harm to the slab. Another classic example is the artificial high load transfer observed when FWD tests are performed at high ambient temperatures (>80oF). Therefore, it is essential to make sure that the difference in temperature and moisture conditions do not have a significant impact on the FWD analysis results to avoid making inaccurate decisions at the network and project levels. This paper presents an effort to account for the impact of daily temperature variation on FWD analysis results for rigid pavements. The work presented in this paper is a part of a large-scale research study sponsored by the New Jersey Department of Transportation (NJDOT) to study the seasonal variation in pavement properties and its impact on pavement response and performance.

A Queueing Theory Approach to Analyze the Impact of COVID-19 Pandemic on Hospitals System Capabilities: A Lesson for Future Pandemic Preparedness

Pandemics are life-threatening and resource-intensive. Hospitals with limited resources saw a surge in patients during pandemics. These situations can result in a large number of casualties in a small time period. The “golden hour” after infection is crucial for treatment and can significantly impact the survival rate. It is inevitable to treat these victims in the “golden hour” to prevent serious loss of lives. Our objective is to enhance the capacity of the healthcare system to treat victims in "golden hours" during pandemics. This article will evaluate the arrival of victims and compare it with the hospital's treatment capabilities. We have created a system known as the "Transient Act System (TAS)." This system identifies overcrowding in hospitals. The M/M/s/GD/c/∞ type multi-channel queueing system is described to calculate the hospital treatment capacity. The hospital capacity calculation method is based on the waiting time probability distribution function, where the patient waiting times follow an Erlang distribution. The suggested method is validated using numerical analysis, including probability distribution and graphical representations. The study ends with suggestions for future research and advice on how to increase the effectiveness of the hospital system in pandemic situations. This study serves as an example that justifies the feasibility. The findings of this study can immediately help policymakers and planners make better decisions about pandemic situations and future health crises.

Gross motor abnormalities in relation to balance and weight indicators in children with spastic diplegia

BackgroundOver the past 10 years, the prevalence of obesity in the cerebral palsy population has increased in the USA, ranging from 7.7 to 16.5%. Obesity is linked to health problems as well as challenges with walking and balance. The current study investigated the correlation between BMI, balance, and gross motor abnormalities in children with diplegia.MethodsThis cross-sectional-correlation study was done at the Outpatient Clinic at the Faculty of Physical Therapy, Cairo University. The study included 104 diplegic children aged from 5 to 10 years, 53 in the normal weight group and 51 in the overweight group. Dynamic balance was evaluated by the overall stability index (OSI) in the Biodex Balance System and gross motor capacities (GMC) were evaluated by standing and walking dimensions in GMFM.ResultsOn comparing outcome variables, there were significant differences among groups in BMI, GMC, and OSI (P < 0.001). Moreover, there was a significant negative strong correlation between GMC and OSI (r = − 0.792 and P < 0.001).ConclusionOverweight and obese diplegic cerebral palsy children have decreased balance and GMC significantly when compared to normal-weight children. There was also a significant correlation between GMC and OSI (r = − 0.792).Trial registrationThe study registered in ClinicalTrial.gov in October 2024 (NCT06642922).

Efficacy of spray flushing in the reprocessing of flexible endoscopes

This article comments on the article by Du et al , who conducted a randomized controlled trial aiming at evaluating the effectiveness of a novel spray flushing system in cleaning flexible endoscopes while minimizing damage to the working channels. We share our perspective on the importance of improving endoscope reprocessing methods. The findings highlight the spray flushing system's capacity to improve cleaning efficacy while minimizing damage, suggesting that it might be important in enhancing endoscope reprocessing procedures.

Resilience Informatics in Public Health: Qualitative Analysis of Conference Proceedings.

In recent years, public health has confronted 2 formidable challenges: the devastating COVID-19 pandemic and the enduring threat of climate change. The convergence of these crises underscores the urgent need for resilient solutions. Resilience informatics (RI), an emerging discipline at the intersection of informatics and public health, leverages real-time data integration from health systems, environmental monitoring, and technological tools to develop adaptive responses to multifaceted crises. It offers promising avenues for mitigating and adapting to these challenges by proactively identifying vulnerabilities and fostering adaptive capacity in public health systems. Addressing critical questions regarding target audiences, privacy concerns, and scalability is paramount to fostering resilience in the face of evolving health threats. The University of Arizona held a workshop, titled Resilience Informatics in Public Health, in November 2023 to serve as a pivotal forum for advancing these discussions and catalyzing collaborative efforts within the field. This paper aims to present a qualitative thematic analysis of the findings from this workshop. A purposive sampling strategy was used to invite 40 experts by email from diverse fields, including public health, medicine, weather services, informatics, environmental science, and resilience, to participate in the workshop. The event featured presentations from key experts, followed by group discussions facilitated by experts. The attendees engaged in collaborative reflection and discussion on predetermined questions. Discussions were systematically recorded by University of Arizona students, and qualitative analysis was conducted. A detailed thematic analysis was performed using an inductive approach, supported by MAXQDA software to manage and organize data. Two independent researchers coded the transcripts; discrepancies in coding were resolved through consensus, ensuring a rigorous synthesis of the findings. The workshop hosted 27 experts at the University of Arizona, 21 (78%) of whom were from public health-related fields. Of these 27 experts, 8 (30%) were from the field of resilience. In addition, participants from governmental agencies, American Indian groups, weather services, and a mobile health organization attended. Qualitative analysis identified major themes, including the potential of RI tools, threats to resilience (eg, health care access, infrastructure, and climate change), challenges with RI tools (eg, usability, funding, and real-time response), and standards for RI tools (eg, technological, logistical, and sociological). The attendees emphasized the importance of equitable access, community engagement, and iterative development in RI projects. The RI workshop emphasized the necessity for accessible, user-friendly tools bridging technical knowledge and community needs. The workshop's conclusions provide a road map for future public health resilience, highlighting the need for scalable, culturally sensitive, community-driven interventions. Future directions include focused discussions to yield concrete outputs such as implementation guidelines and tool designs, reshaping public health strategies in the face of emerging threats.

Methods and Practical Considerations for Conducting Budget Impact Analysis for Non-Pharmaceutical Interventions.

Health technology assessment (HTA) can be conducted at the national, provincial, or hospital level. Although provincial and hospital-based HTAs often focus on non-pharmaceutical interventions, budget impact analysis (BIA) methods for non-pharmaceutical interventions have received less attention in the literature. We reviewed HTAs of non-pharmaceutical interventions published since 2015 by a Canadian provincial HTA agency, evaluating the characteristics and challenges of conducting a BIA. We summarized the unique characteristics of BIAs for different categories of interventions, including surgery and other procedures, diagnostic or screening tests, therapeutic programs, and digital health technologies. We then discussed specific methodological and practical considerations for conducting a BIA of a surgical or other hospital-based procedure. Critical points for BIA methods include the following: (1) when estimating the size of a target population, healthcare system capacity must be accounted for, and historical volumes may offer more realistic figures than prevalence and incidence rates; (2) factors that affect the uptake of a new intervention include guideline recommendations, labor and infrastructure requirements for implementation, and the target population size; (3) when interpreting a budget impact that shows cost savings, analysts must address where the savings are generated from and whether they can be reallocated. Some of the considerations discussed may also apply to HTAs of pharmaceuticals. When conducting a BIA of a non-pharmaceutical intervention, addressing these methodological considerations may help in better predicting the financial impact of the new intervention for the public payer and guide appropriate budget allocation for healthcare system planning.

Modeling, Design, and Laboratory Testing of a Passive Friction Seismic Metamaterial Base Isolator (PFSMBI)

This paper focuses on the theoretical and analytical modeling of a novel seismic isolator termed the Passive Friction Mechanical Metamaterial Seismic Isolator (PFSMBI) system, which is designed for seismic hazard mitigation in multi-story buildings. The PFSMBI system consists of a lattice structure composed of a series of identical small cells interconnected by layers made of viscoelastic materials. The main function of the lattice is to shift the fundamental natural frequency of the building away from the dominant frequency of earthquake excitations by creating low-frequency bandgaps (FBGs) below 20 Hz. In this configuration, each unit cell contains an inner resonator that slides over a friction surface while it is tuned to vibrate at the fundamental natural frequency of the building. This resonance enhances the energy dissipation capacity of the PFSMBI system. After deriving the governing equations for four selected lattice configurations (i.e., Cases 1–4), a parametric study is performed to optimize the PFSMBI system for a wide range of harmonic ground motion frequencies. In this study, we examine how key parameters, such as the mass ratios of the cells and resonators, tuning frequency ratios, the number of cells, and the coefficient of friction, affect the system’s performance. The PFSMBI system is then incorporated into the dynamic model of a six-story base-isolated building to evaluate its effectiveness in reducing the floor acceleration and inter-story drift under actual earthquake ground motion records. This dynamic model is used to investigate the effect of stick–slip motion (SSM) on the energy dissipation performance of a PFSMBI system by employing the LuGre friction model. The numerical results show that the optimized PFSMBI system, through its lattice structure and frictional resonators, effectively reduces floor acceleration and inter-story drift by leveraging FBGs and frictional energy dissipation, particularly when SSM effects are properly accounted for. Finally, a small-scale prototype of the PFSMBI system with two cells is developed to verify the effect of SSM. This experimental validation highlights that neglecting SSM can lead to an overestimation of the energy dissipation performance of PFSMBI systems.

Improvement of Internet of Things (IoT) Interference Based on Pre-Coding Techniques over 5G Networks

The advent of 5G technology has revolutionized wireless communication, offering unprecedented data rates, reduced latency, and enhanced connectivity. A critical component driving these advancements is Multiple-Input Multiple-Output (MIMO) technology. MIMO utilizes multiple antennas at both the transmitter and receiver ends to improve communication performance. In the context of the Internet of Things (IoT), MIMO plays a pivotal role in enhancing network efficiency, reliability, and capacity and can improve system capacity and reduce interference between different users. By leveraging MIMO, IoT devices can achieve higher data throughput and better signal quality, even in challenging environments. This is particularly important for IoT applications that require real-time data transmission and low latency, such as smart cities, autonomous vehicles, and industrial automation. Additionally, MIMO technology helps in mitigating interference and improving spectrum utilization, making it an essential enabler for the massive connectivity demands of IoT networks in the 5G era. However, due to the high channel dimension, complex channel estimation and precoding algorithms in the system, the system hardware and software overhead will increase. The precoding algorithms of massive MIMO systems are divided into three types: digital, analog and hybrid. The three types of precoding algorithms are summarized and compared, and the advantages and disadvantages of different precoding algorithms and applicable scenarios are summarized. The channel estimation schemes are divided into training estimation and blind estimation, and the advantages and disadvantages of the two types of schemes are summarized. It is pointed out that the reasonable use of the channel sparsity of massive MIMO can improve the quality of channel estimation and reduce the estimation overhead.

Capacity optimization of photovoltaic storage hydrogen power generation system with peak shaving and frequency regulation

To solve the problem of power imbalance caused by the large-scale integration of photovoltaic new energy into the power grid, an improved optimization configuration method for the capacity of a hydrogen storage system power generation system used for grid peak shaving and frequency regulation is proposed. A hydrogen storage power generation system model is established, and the photovoltaic power generation and hydrogen fuel cell power generation is calculated. A two-layer hydrogen storage power generation system capacity optimization configuration model was established, an improved particle swarm optimization algorithm was used to solve the improved hydrogen storage power generation system capacity optimization configuration model, and the capacity optimization configuration results were obtained. The experimental results show that this method can obtain the best capacity allocation result based on local lighting conditions and the cost of the power generation system, whereas the improved particle swarm optimization algorithm can solve the model faster and reduce the cost of the power generation system. After applying this method, the net income of the solar hydrogen storage power generation system has almost doubled.

A Review of Health Monitoring and Model Updating of Vibration Dissipation Systems in Structures

Given that numerous countries are located near active fault zones, this review paper assesses the seismic structural functionality of buildings subjected to dynamic loads. Earthquake-prone countries have implemented structural health monitoring (SHM) systems on base-isolated structures, focusing on modal parameters such as frequencies, mode shapes, and damping ratios related to isolation systems. However, many studies have investigated the dissipating energy capacity of isolation systems, particularly rubber bearings with different damping ratios, and demonstrated that changes in these parameters affect the seismic performance of structures. The main objective of this review is to evaluate the performance of damage detection computational tools and examine the impact of damage on structural functionality. This literature review’s strength lies in its comprehensive coverage of prominent studies on SHM and model updating for structures equipped with dampers. This is crucial for enhancing the safety and resilience of structures, particularly in mitigating dynamic loads like seismic forces. By consolidating key research findings, this review identifies technological advancements, best practices, and gaps in knowledge, enabling future innovation in structural health monitoring and design optimization. Various identification techniques, including modal analysis, model updating, non-destructive testing (NDT), and SHM, have been employed to extract modal parameters. The review highlights the most operational methods, such as Frequency Domain Decomposition (FDD) and Stochastic Subspace Identification (SSI). The review also summarizes damage identification methodologies for base-isolated systems, providing useful insights into the development of robust, trustworthy, and effective techniques for both researchers and engineers. Additionally, the review highlights the evolution of SHM and model updating techniques, distinguishing groundbreaking advancements from established methods. This distinction clarifies the trajectory of innovation while addressing the limitations of traditional techniques. Ultimately, the review promotes innovative solutions that enhance accuracy, reliability, and adaptability in modern engineering practices.

A fundamental rheological approach to determine the optimum water absorption capacity of a model gluten-free dough system: soy flour dough.

Determining the optimum water absorption capacity of gluten-free flours for an improved breadmaking process has been a challenge because there is no standard method. In the present study, large amplitude oscillatory shear (LAOS) tests were performed to explore the impact of different levels of added water on non-linear viscoelastic response of soy flour dough in comparison to wheat flour dough at a consistency of 500 BU. Among the LAOS parameters, large strain modulus (G'L) and large strain rate viscosity (η'L) were found to better probe the impact of added water amount on non-linear viscoelastic properties of soy flour dough. Although soy flour dough with 160:100 (water: soy flour, v/w) and wheat flour dough had overlapping η*(ω) in the linear viscoelastic region, LAOS sweeps revealed similar tan δ, G'L and η'L values along with similar elastic and viscous Lissajous-Bowditch curves at γ0 = 200% for soy flour dough with 175:100 (water: soy flour, v/w) to those of wheat flour dough. Considering the large deformations involved in breadmaking process and the poor capability of the linear viscoelastic measures to predict loaf volume, the present study suggests using the LAOS parameters to determine the optimum water absorption capacity and to optimize the strain-stiffening and shear-thinning behaviors of gluten-free flours to improve end-product quality. © 2025 Society of Chemical Industry.

Addressing evidence needs during health crises in the province of Quebec (Canada): a proposed action plan for rapid evidence synthesis

BackgroundThe COVID-19 pandemic necessitated the rapid availability of evidence to respond in a timely manner to the needs of practice settings and decision-makers in health and social services. Now that the pandemic is over, it is time to put in place actions to improve the capacity of systems to meet knowledge needs in a situation of crisis. The main objective of this project was thus to develop an action plan for the rapid syntheses of evidence in times of health crisis in Quebec (Canada).MethodsWe conducted a three-phase collaborative research project. First, we carried out a survey with producers and users of rapid evidence syntheses (n = 40) and a group interview with three patient partners to prioritize courses of action. In parallel, we performed a systematic mapping of the literature to identify rapid evidence synthesis initiatives developed during the pandemic. The results of these two phases were used in a third phase, in which we organized a deliberative workshop with 26 producers and users of rapid evidence syntheses to identifying strategies to operationalize priorities. The data collected at each phase were compared to identify common courses of action and integrated to develop an action plan.ResultsA total of 14 specific actions structured into four main axes were identified over the three phases. In axis 1, actions on raising awareness of the importance of evidence-informed decision-making among stakeholders in the health and social services network are presented. Axis 2 includes actions to promote optimal collaboration of key stakeholders in the production of rapid evidence synthesis to support decision-making. Actions advocating the use of a variety of rapid evidence synthesis methodologies known to be effective in supporting decision-making are presented in axis 3. Finally, axis 4 is about actions on the use of effective knowledge translation strategies to promote the use of rapid evidence synthesis products to support decision-making.ConclusionsThis project led to the development of a collective action plan aimed at preparing the Quebec ecosystem and other similar jurisdictions to meet knowledge needs more effectively in times of health emergency. The implementation of this plan and its evaluation will enable us to continue to fine-tune it.

Enhancing the control of respiratory virus spread: a comprehensive approach integrating airborne virus detection, aerological investigations, and airflow modeling for practical implementation.

Patients with chronic kidney disease suffer from immune dysfunction, increasing susceptibility to infections. The aim of the study was to investigate air contamination with respiratory viruses in a dialysis unit at a quaternary hospital using molecular detection techniques and to analyze airflow dynamics through computational fluid dynamics (CFD) simulations for a comprehensive assessment of air transmission risks. We conducted dialysis unit air sampling using AerosolSense™ samplers. Air and clinical sampling occurred during three periods in 2022: winter, early, and late fall. A technical team maintained the dialysis unit's ventilation system during mid fall. Ventilation system capacity and airflow rates were measured. CFD simulations were used to evaluate airflow dynamics. The investigation collected 144 air samples, revealing heterogeneous virus detection rates across locations and study periods. Virus positivity correlated with the presence of patients and the effectiveness of the ventilation system. The ratio of virus air positivity to virus patient positivity was 1.84 and 3.35 during the first and the second periods, respectively, and collapsed to 0.64 after maintenance. Airflow rate measurements highlighted a ninefold discrepancy between actual and theoretical airflow (393 m3/h vs. 3530 m3/h), which was rectified by maintenance actions. Airflow dynamics and particle dispersion visualization through CFD simulations contributed to a better understanding of transmission risks. Detection of viruses in the air, combined with CFD, revealed deficiencies in air renewal. Maintenance interventions significantly improved airflow dynamics and particle dispersion, reducing airborne virus spread.

A Mechanism Framework for Clearing Prices in Electricity Market Based on Trusted Capacity of Power Generation Resources

A reasonable capacity market mechanism is conducive to exploring the capacity value of different power generation resources and ensuring the adequacy of power supply capacity in power systems. In response to the challenges faced by the existing capacity market mechanism under the background of energy transformation, such as the unreasonable quantification of the support effect of different power generation resources on the power capacity of power system and the imperfect pricing mechanism of power capacity, a capacity market mechanism for power systems with high proportion renewable energy has been designed. To quickly clarify the capacity support effect of different power generation resources, a capacity credibility factor is introduced to quantify the actual contribution of different power generation resources in capacity supply and to deeply explore the capacity value of power generation resources. Based on the uniform marginal clearing price in the capacity market, the marginal clearing price of different power generation resources is corrected by using the cost ratio factor, which includes the difference in the cost structure of power generation resources. By comparing and analyzing examples, the proposed cost ratio factor can effectively optimize the capacity price; the maximum price difference is 18.2 yuan/MW, the overall capacity cost of the system is reduced by 53.70%, and the effective connection between fixed cost and variable cost of power generation resources is realized.

Improved cooling capacity of a magnetic refrigeration system using milled gadolinium chips

Improved cooling capacity of a magnetic refrigeration system using milled gadolinium chips

Valproic acid ameliorates morpho-dysfunctional effects triggered by Ischiatic nerve crush injury-induced by compression model in mice: nerve regeneration and immune-modulatory pathway

Peripheral nerve injuries are extremely severe and may lead to permanent disability, despite the regenerative capacity of the peripheral nervous system (PNS). To date, there is no established pharmacological therapy capable of predicting functional recovery and alleviation of trauma-related symptoms such as neuropathic pain, inflammation and weakness, which are the main targets for current therapies. In this work we provide new evidence for a therapeutic use of valproic acid (VPA) upon ischiatic nerve injury. Ischiatic nerve-injured mice treated with VPA after lesion, displayed an improvement in pain and motor function associated with an increase in the number of myelinated nerve fibers, and exhibited a more organized microenvironment during regeneration. In addition, VPA treatment also promoted an immunomodulatory capacity, leading to a significant enhancement of neutrophils in the peritoneal cavity, suggesting its role on the sensory and motor recovery after ischiatic nerve injury. This highlights the physiological role of VPA during ischiatic nerve regeneration and contributes to the characterization of innovative pharmacological epigenetic therapy capable of accelerating peripheral nerve regeneration with critical impacts on the clinical practice.

Effects of contract-based trading mechanism of power flexibility on hosting capacity of distribution systems

Effects of contract-based trading mechanism of power flexibility on hosting capacity of distribution systems

Local structure and thermophysical properties of the molten salt FNaBe through ab initio molecular dynamics and experimental measurements

NaF-BeF2 molten salt has been proposed as one of the potential solvents and coolants for molten salt reactor due to its pertinent properties and satisfactory neutron capture cross-section. The experimental measurements combined theoretical simulations were employed to investigate comprehensive information on the structures and thermophysical properties of molten NaF-BeF2. Specifically, the specific heat capacity, density, and viscosity of NaF-BeF2 systems were determined using custom devices. Using the fitting relationships and simulations, the extrapolative data were also successfully obtained under the critical temperatures. The local structure including bond lengths, coordination structures and the potential of mean force, was further simulated by ab initio molecular dynamics in the temperature range of 673-1123 K. The coordination of Na and Be is predominantly characterized by six-fold and four-fold, respectively. Moreover, of Be-F bond is 7 times than Na-F bond, which suggests the stronger stability of Be-F bond in molten NaF-BeF2.

Water immersion impact on the durability of Fe-SMA/steel joints used in reinforcement systems

Adhesively attaching iron-based shape memory alloy (Fe-SMA) to repair cracks in existing buildings represents a novel and effective approach to extending their service lives. The bond behavior between Fe-SMA and these parent buildings is crucial for the safety of reinforcement systems. Under hot-humid environments, the bond capacity of these reinforcement systems deteriorates, making the durability and reinforcement efficiency questionable. This study evaluates the distribution and progressive propagation of Fe-SMA strain and interface shear stress within the lap zone, as well as the failure behavior of Fe-SMA/steel single strap joints (SSJs) exposed to 55 °C running water. Based on experimental results, the bond-slip models of SSJs with various adhesive types and aging durations immersed in running water are proposed. As the aging duration extends, the maximum Fe-SMA strain and interface shear stress of SSJs decrease. The maximum shear stress of Type-AI SSJs at aging durations of 30, 60, and 90 days are 14.69, 11.89, and 9.66 MPa, respectively. Similarly, for Type-AII, the maximum shear stress at the same aging durations are 15.09, 11.26, and 8.82 MPa, respectively. When the aging duration increases from 30 to 90 days, the effective lap length of Type-AI and Type-AII SSJs improves by 13.33 % and 18.75 %, respectively. The maximum errors for cubic and bilinear bond-slip models in estimating fracture energy under harsh environments are 12 % and 16 %, respectively. After 90 days of exposure to running water, the fracture energy of Type-AI and Type-AII SSJs reduces by approximately 83 % and 88 %, respectively. This research offers guidelines for the durability of existing buildings strengthened with bonded Fe-SMA, reducing maintenance costs.

Differences for Cooling Capacity of a Cable Tunnel System: Install One or Three Additional Cable Troughs with Cable Circuit for 100/70 Heat Loads – A Numerical Study

The purpose of this report was to compare the numerical analysis for different cooling efficiency of a cable tunnel system when installing one additional cable trough or three cable troughs for cable circuit 100% or 70% heat load. Cable tunnel system is widely known for it is use for high voltage transmission in an underground. Due to the cables generating large quantities of heat, water pipes and air ventilation were used in the tunnel to cool down the transmission cable. To investigate the cooling efficiency of a tunnel, research for benchmark case was carried out. A Computational Fluid Dynamic (CFD) benchmark analysis about 2D natural convection inside the square cavity was investigated to further understand the air movement inside the square medium. Ansys Fluent was carried out for benchmark cases of heat transfer natural convection inside the square cavity and to check whether Ansys Fluent can be used for any CFD and heat transfer purposes by validating the results with previous studies. The benchmark case used a 2D square with different active temperature side walls and adiabatic walls for top and bottom side. From the benchmark simulations with different Rayleigh Number, a number representing buoyancy-driven of a fluid from 103 to 105 affected air differently and the heat transfer natural convection inside the square. At different Rayleigh Number air forms a recirculation passing the active walls and adiabatic walls. After investigated the benchmark, the results were used to validate with previous studies. To validate the results was by using Nusselt Number, ratio of convective to conductive. The benchmark case results were validated and Ansys Fluent proven can be used for CFD and heat transfer purposes. Two 3D cable tunnel were modelled with 100-meter length after concluded the benchmark. The two tunnel models were based on the number of cable troughs installed. The first tunnel was with one cable trough and two cable circuits on the bottom, as for the second tunnel was with one bottom cable circuit and three cable troughs. Cable tunnel simulations were based on cable circuit for 100% heat load and 70% heat load with each heat load case was given different water flow rate of 4.25 L/s and 6.5 L/s. A total of eight scenario cases were carried out to determine which provided a better cooling efficiency choice. The analysis for cable tunnel cases on how the copper cables cooled down through heat transfer of natural convection inside the cable trough, which the heat then was removed from the cable circuit by air and continue to the outside of the tunnel. During the heat transfer processes, conductivity was present as not all heat were removed by air and water, but continue to through the walls of the tunnel and to the ground soil. Based on the simulations, a cable tunnel with three cable troughs was proven more cooling efficiency compared tunnel with one cable trough. Some scenarios did not meet the criteria, due to insufficient heat relocation by air and water. The cooling efficiency was determined by which has the better balance heat relocation by air, water, and ground, also considering the comfort and safety of human inside the tunnel.