Analysis Of Experiments Research Articles

Tracking the terminal velocity and energy of a parachutist: A video analysis for Physics classroom experiment

Abstract This study primarily focuses on tracking a parachutist’s terminal velocity and energy during a free fall using video analysis. Also, this study looks into related literature about the implications of this experiment for classroom practice. High-quality and slow-motion videos of free-falling slotted masses acting as parachutists were captured, and the terminal velocities and energies were analyzed through software tracker video analysis and modeling. The data from the software revealed that, indeed, the terminal velocity is directly proportional to the square root of the masses. The 200g parachutist reaches terminal velocity first, then the less massive parachutist. The generated kinetic energy, gravitational potential energy, and total mechanical energy graphs were similar to the literature. The tracker video analysis can indeed track a parachutist’s terminal velocity and energy. However, the acceleration due to gravitational needed to be measured correctly due to some errors in the experiment. Furthermore, the literature has cited positive and negative implications for classroom practice. This study can say that the positive outweighs the negative. The positive repercussions were about enhanced engagement, accuracy, and data precision, while the negative ones were about the school’s technological divide.

Investigation of the optimal timing and amount of fuel injection on the efficiency and emissions of a diesel engine through experimentation and numerical analysis

The purpose of this study is to investigate the performance, in-cylinder combustion, and emissions of the MTE660E heavy-duty diesel engine using 3D CFD simulation. The CFD simulation model based on AVL FIRE software was developed to numerically investigate the performance, in-cylinder combustion, and emissions of the MTE660E engine. The AVL model was validated against empirical data. The 6-cylinder MTE660E engine was operated under a constant excess air ratio of 1.75 and at 1600 rpm engine speed. The geometry and lattice design of the MTE660E engine were simulated to provide a computationally efficient approach. The AVL model was validated against experimental data and the error between the measured and calculated value of combustion characteristics and emissions was acceptable (R2> 90 %), error <5.6 %). Design Expert software was used to optimize the dependent variables (peak chamber temperature, brake mean effective pressure, engine torque, engine thermal efficiency and emissions of NOx) according to the studied variables (injection time and fuel injection quantity) based on response surface methodology. The results show that the recommended injecting time of 342 °C and the specific amount of fuel lead to better combustion efficiency, resulting in high engine performance and low emissions. The specific fuel consumption was highest at 2200 rpm with a 50 % load, while the lowest SFC level was observed at 1750 rpm with a 100 % load. The maximum value of NOx emissions was observed at full load. The findings show that the optimization of the injection timing and fuel injection quantity can effectively enhance the performance of the MTE660E engine. The study provides valuable insights into improving combustion efficiency, resulting in greater performance and reduced emissions without requiring expensive overhaul. It has potential applications in automotive and commercial transportation industries, thereby reducing fuel consumption and emissions.

Temporal asymmetries in inferring unobserved past and future events

Unlike temporally symmetric inferences about simple sequences, inferences about our own lives are asymmetric: we are better able to infer the past than the future, since we remember our past but not our future. Here we explore whether there are asymmetries in inferences about the unobserved pasts and futures of other people’s lives. In two experiments (analyses of the replication experiment were pre-registered), our participants view segments of two character-driven television dramas and write out what they think happens just before or after each just-watched segment. Participants are better at inferring unseen past (versus future) events. This asymmetry is driven by participants’ reliance on characters’ conversational references in the narrative, which tend to favor the past. This tendency is also replicated in a large-scale analysis of conversational references in natural conversations. Our work reveals a temporal asymmetry in how observations of other people’s behaviors can inform inferences about the past and future.

Безусловный базовый ДОХОД VS социальная справедливость: возможно ли единство?

Every year, the issue of implementing the principles of social justice becomes more and more relevant. In this regard, the concept of unconditional basic income is beginning to gain popularity in many countries, designed to solve many problems of a socio-economic nature. The purpose of the work is to identify the effectiveness of the introduction of an unconditional basic income in order to ensure the implementation of the principles of social justice. The main methods used in the study include analysis and evaluation of analytical and statistical materials, their comparison, a dialectical approach to analyzing the information base of the study, as well as scenario analysis. As a result of the work done by the authors, it was revealed that the existing projects for the introduction of universal transfers cannot be fully called equivalent analogues of a full-fledged program for the provision of unconditional basic income. As a result, at the moment it is not possible to draw specific conclusions about the consequences of implementing such a policy of «equality of results». Nevertheless, based on the analysis of such experiments, key factors influencing the real consequences of the introduction of universal transfers have been identified. These include the amount of unconditional payments, as well as the salary level formed in the context of the implementation of the concept under study. Therefore, further identification of the consequences of providing universal payments in the process of modeling possible scenarios for the introduction of unconditional basic income was based on these factors. Based on the analysis, it was concluded that the introduction of an unconditional basic income can lead to many negative consequences. In this regard, the authors propose to pay attention to the possibility of implementing the principle of «equality of opportunities» for the entire population. The results of this study can be used in the future in order to find new ways to improve the socio-economic policy of the country to improve the well-being of its population.

Enhancing Full Waveform Inversion of Field GPR Data: A Source-Independent Approach with Dynamic Reference Selection via SE-Wave-U-Net

Ground Penetrating Radar (GPR) is a widely-utilized non-destructive detection tool. Full Waveform Inversion (FWI) offers a reliable algorithm for accurately imaging GPR data. Despite its potential, FWI's effectiveness is often compromised by unknown excitation sources, which can lead to computational failures and/or diminished imaging accuracy. Addressing this challenge, this paper introduces a convolution-type objective function designed to mitigate the detrimental effects of these unknown excitation sources on FWI imaging. Critical to the success of this function is the precise selection of reference traces. Further refining the capability for signal separation, we have integrated Squeeze-and-Excitation (SE) modules into the traditional Wave-U-Net architecture, culminating in the development of the SE-Wave-U-Net framework. This framework is adept at dynamically extracting accurate reference traces from field GPR data, which are essential for the accurate FWI imaging. The efficacy, accuracy, and practical applicability of proposed methods are validated through extensive analysis of numerical, laboratory experiments, and field GPR data. The proposed algorithm not only establishes a high-precision computational framework for FWI but also enhances the reliability of GPR imaging in complex environments.

Effects of Plant Extracts on Growth Promotion, Antioxidant Enzymes, and Secondary Metabolites in Rice (Oryza sativa) Plants

Plant extracts are widely used in sustainable agriculture practices to enhance crop production and reduce chemical usage in agriculture. This study employed several extraction solutions of various plant extracts to synthesize planting and spraying strategies, assess the persistence efficacy of rice, and investigate the influence of selected water extracts on secondary chemicals at different rice planting stages. Among 17 water extracts that were evaluated on rice seeds, 7 were enhanced to align with the lengths of rice roots 50–70% and shoots 40–50%. The analysis of extraction, spraying, and planting experiments revealed that water extracts, soil application, and transplanting were the most efficient methods for stimulating rice growth, especially 0.1 and 0.5% concentrations. The efficacy of the extracts remained intact also after 14 days of treatment. This study showed that photosynthesis and antioxidant activities may play crucial roles in plant growth. Rice growth stimulation has been linked to photosynthesis, flavonoid contents, and antioxidant enzymes, providing a balanced supply of nutrients for plant growth. Among all tested water extracts, Psidium guajava, Aloe vera, Allium sativum, and Medicago sativa extracts can be used to promote plant growth in organic farming.

Insight into the micro-mechanism of hydrate-based methane storage from active ice

Gas hydrate formation in active ice holds significant potential for solidified natural gas storage, while the deep understanding of its micro-mechanism is required for the futural application of such a technology. In this study, the kinetics and micro-properties of methane hydrate formation enhanced by active ice (porous ice containing an unfrozen solution layer of sodium dodecyl sulfate) were investigated via experiments and molecular dynamics (MD) simulations. Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray diffraction (XRD) differential scanning calorimetry (DSC) characterization, and in-situ visual observation confirmed the formation of sI methane hydrate in the active ice system and the occurrence of single-crystal hydrate, and also indicated the occurrence of active water near the surface of porous active ice during the active ice formation. A sensitivity analysis of the hydrate kinetics experiments suggested that temperature is the primary driver of rapid methane hydrate formation in the active ice system. The shortest induction time and t90 for hydrate formation were recorded at 5 s and 5.5 min, respectively. Furthermore, MD simulations indicated that the direct hydrate nucleation and growth in the active water, heat transfer from gas hydrate to ice, and the diffusion of active water (1.24 × 10-9 m2/s) and methane (7.10 × 10-8 m2/s) into the porous ice structure are the primary mechanism that enhances hydrate formation kinetics and methane storage capacity. This work provides an essential microscopic mechanism of the “active ice → active water → gas hydrate” circulation that contributes to the deep understanding and futural application of the efficient hydrate-based solidified methane storage in active ice system.

Research Progress on the Mechanisms and Control Methods of Rockbursts under Water–Rock Interactions

Rock bursts are among the most severe and unpredictable hazards encountered in deep rock engineering, posing substantial threats to both construction safety and project progress. This study provides a comprehensive investigation into how moisture infiltration influences the propensity for rock bursts, aiming to establish new theoretical foundations and practical methods for their prevention. Through the analysis of meticulous laboratory mechanical experiments and sophisticated numerical simulations, we analyzed the variations in the physical and mechanical properties of rocks under different moisture conditions, with a particular focus on strength, brittleness, and energy release characteristics. The findings reveal that moisture infiltration significantly diminishes rock strength and reduces the likelihood of brittle fractures, thereby effectively mitigating the risk of rock bursts. Additionally, further research indicates that in high-moisture environments, the marked reduction in rock burst tendency is attributed to increased rock toughness and the suppression of crack propagation. This study advocates for the implementation of moisture control measures as a pre-treatment strategy for deep rock masses. This innovative approach presents a viable and effective solution to enhance engineering safety and improve construction efficiency, offering a practical method for managing rock burst risks in challenging environments.

Experimental Design for Optimization of Felbamate Nanosuspension Using Box-Behnken Design.

Felbamate, a valuable antiepileptic drug, suffers from low water solubility and potential side effects, limiting its therapeutic application. This study addresses this challenge by developing a felbamate nanosuspension for nose-to-brain delivery using a three-factor, three-level Box-Behnken design. The research focused on identifying the optimal combination of key formulation variables, chitosan concentration, chitosan/sodium tripolyphosphate ratio, and Tween 80 surfactant concentration to achieve a nanosuspension with desirable particle size, polydispersity index, and high entrapment efficiency (%EE), all critical parameters for efficient drug delivery via the nasal route. The study identified an optimized formulation consisting of 0.176% chitosan, a 3.3:1 chitosan/TPP ratio, and 1.55% Tween 80 through rigorous experimentation and response surface methodology analysis. The optimized formulation yielded a nanosuspension of 115.0 ± 4.37 nm mean particle size, 0.118 ± 0.021 polydispersity index, and +34.08 ± 2.4 mV zeta potential, indicating a stable system with a narrow size distribution suitable for enhanced drug delivery. The entrapment efficiency of 93.18 ± 1.69% confirmed effective encapsulation, while in-vitro dissolution studies demonstrated a significantly higher dissolution rate compared to pure felbamate, suggesting improved bioavailability. The results emphasize the capacity of this optimized nanosuspension to improve the therapeutic efficacy of felbamate and hence justify additional preclinical and clinical research.

Photocatalytic applications of metal oxide-based nanocomposites for sustainable environmental remediation

Change in human lifestyle and excessive use of commercial products have caused an ecological deterioration. A major contribution towards this comes from the mixing of toxins and persistent organic pollutants into water bodies, which poses a serious risk to the ecosystem. In the above context, materials scientists are involved in the search for sustainable solutions to address the above environmental challenges by the development of advanced materials. In this study, we prepared nanocomposite materials such as; ZnO-SnO2 and ZnO-MoS2 by wet-chemical approach to degrade dye pollutants like Rhodamine B (RhB) and Congo red (CR) towards achieving environmental remediation. Powder X-ray diffraction (PXRD) measurement was done for structural characterization of the samples and the formation of the nanocomposite phase was validated by the above study. The goal of the field emission scanning electron microscopy (FESEM) study was to examine the morphology of the composites which was accompanied by the energy dispersive analysis of x-rays (EDAX) and electron mapping experiments which verified the presence of Zn, Sn, O, Mo, S elements in the respective samples. Fourier transformed infrared spectroscopy (FTIR) meas urement was conducted to investigate the vibrational properties of the samples. Photocatalytic measurement showed improved degradation efficiency of the composites as compared to the pristine samples. The degradation efficiency was found to increase with irradiation time and attained saturation after 180 min. ZnO-SnO2 nanocomposite show 91.23 % and 88.11 % of degradation for RhB and CR dyes respectively whereas 89.29 % and 83.25 % degradation have been obtained for ZnO-MoS2 for the same dyes. Several aspects of the experiment were varied, including the amount of catalyst employed, the initial dye concentration, and the pH levels, in order to assess the efficacy of the photocatalysts. Both the photocatalysts degraded CR dye most effectively at acidic pH, although RhB dye gets degraded more at neutral and alkaline pH. ZnO-SnO2 was found to be an effective photocatalyst for degrading RhB dye at neutral pH and CR dye at acidic pH. After multiple iterations of experimentation, the photocatalytic mechanism has been extensively described, and the stability and reusability of the photocatalysts have been ensured for effective environmental cleanup.

Ammonia-Cyanuric Acid Co-Production in Boiler Denitrification System.

In response to the issues of poor economic efficiency and high CO2 emissions in the urea-to-ammonia technology of thermal power plants, this paper innovatively proposes a new ammonia production process for thermal power plants. This process utilizes the waste heat of thermal power plant boilers and conducts urea pyrolysis through two-stage heating to prepare ammonia and cyanuric acid. From this, the prepared ammonia can be used in the denitrification process of thermal power plants, and the prepared cyanuric acid can bring additional benefits to thermal power plants. The optimal process scheme was determined through orthogonal experiments of urea pyrolysis. And with the help of Aspen Plus software, a whole-process modeling analysis of urea pyrolysis experiments was carried out to investigate the influences of the melting temperature, melting time, reaction temperature, and reaction time on the process. The results show that when the melting temperature was 160 °C, the melting time was 45 min, the reaction temperature was 240 °C, and the reaction time is 20 min, which was the best scheme, 18.45% ammonia and 52.35% cyanuric acid could be obtained. Through the combined analysis of the Aspen Plus simulation and urea pyrolysis experiments, it was found that the melting temperature should be controlled within 160-167 °C, the melting time should be controlled within 40-45 min, the reaction temperature should be controlled within 240-245 °C, and the reaction time should be controlled within 15-20 min. Compared with the existing urea-to-ammonia process, this process has the advantages of nearly zero emissions and good economic benefits, thus providing reliable research data support for future industrialization.

Multigenerational hormetic effects of different insecticides on Spodoptera frugiperda (J.E. smith) (Lepidoptera: Noctuidae)

To protect crops from pest insects, farmers continuously use insecticides, which eventually degrade into residue due to abiotic or biotic factors. These residual effects of pesticides may cause low lethal and/or sublethal impacts on the exposed pest insect populations, leading to the induction of pest resurgence through hormesis and ultimately the development of resistance. Hormesis is a beneficial bi-phasic effect generally characterized by low-dose reproductive stimulation and high-dose inhibition. In the present study, we investigated the impact of low lethal and sublethal concentrations (LC10, LC20, and LC30) of spinetoram, chlorantraniliprole, and thiodicarb on the F0 generation as well as their multigenerational hormesis effects on the F1 and F2 generations of Fall Armyworm (FAW), Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae). The study focused on reproductive parameters, fecundity, fertility, and life index parameters such as net reproductive rate (R0), intrinsic rate of increase (rm), finite rate of increase (λ), mean length of generation (Tc), and gross reproductive rate (GRR). Fecundity of S. frugiperda increased by 4.82%, 4.63% and 4.58%, while eggs fertility improved by 7.77%, 6.78% and 6.52% at LC10 of thiodicarb, chlorantraniliprole and spinetoram, respectively, from the F1 to F2 generation. Further, interaction analysis (Concentration × Insecticidal treatments) revealed that important vital parameters like pre-oviposition period (POP), oviposition period (OP), post-oviposition period (PtOP), R0,rm,λ, Tc and GRR of F0 were negatively impacted by LC30 of all the tested insecticides and LC20 of only spinetoram. However, LC10 of any of the tested insecticides did not affect these parameters when compared with control. Furthermore, interactive analysis in multigenerational exposure experiments (Concentration × Insecticidal treatments × Generation(s)) showed hermetic effects of LC10 of all tested insecticides which is more positive in F2 as compared to F1 generation. These unwanted positive hermetic effects of low lethal concentrations (LC10) of tested insecticides in offspring of exposed parental population of S. frugiperda indicated its resistance and/or resurgence. Furthernore, present study emphasizes the necessity for additional research to elucidate the underlying mechanisms responsible for these effects.

Effect of solution environment on the binding properties of ruthenium(II) complexes [Ru(bim)2(7-CH3-dppz)]2+ and [Ru(bim)2(dppx)]2+ with double-stranded RNA poly(A)·poly(U)

Two new ruthenium(Ⅱ) complexes containing the same ancillary ligands and different intercalating ligands, [Ru(bim)2(7-CH3-dppz)]2+ (Ru1, bim = 2,2′-biimidazole, 7-CH3-dppz = 7-methyl-dipyrido-[3,2-a,2′,3′-c]-phenazine) and [Ru(bim)2(dppx)]2+ (Ru2, dppx = 7,8-dimethyldipyridophenazine), have been synthesized and characterized in this work, and the interactions of Ru1 and Ru2 with double-stranded RNA poly(A)·poly(U) have been comparatively studied under both dilute and molecular crowding conditions. Analysis of spectral titrations and viscosity experiments as well as thermal denaturation experiments suggests that although complexes Ru1 and Ru2 in both dilute and molecular crowding solutions bind to poly(A)·poly(U) via intercalation, while the binding and stabilizing effects of the two complexes toward poly(A)·poly(U) under molecular crowding conditions significantly decreases in comparision with those in dilute solutions, suggesting that molecular crowding has a significant weakening effect on the interaction of the two complexes with poly(A)-poly(U). The results obtained will contribute to the understanding of the effects of molecular crowding conditions on the binding and stabilization of double-stranded RNA by metal complexes, in particular Ru(II) complexes.

Coalescence time of ellipsoidal-wobbling bubbles at surfactant-free interface: Experimental analysis and collision criteria

This work experimentally analyzed bubbles' coalescence with an air-water interface in the ellipsoidal-wobbling regime for different bubble approach velocities, encompassing the ranges of Eötvös, Weber, and Reynolds numbers of 2-3, 1-4, and 500-1100, respectively. We employed high-speed imaging to measure the bubbles' size, shape, velocity, coalescence time, and number of bounces at the interface. We investigated two criteria to determine the beginning of bubble-interface interaction (“collision”): the physical criterion, based on the distance between the bubble top surface and the interface, and the hydrodynamic criterion, based on the bubble velocity. Gamma distributions represented the coalescence times of bubbles at their terminal velocities well. We found a linear relationship between the coalescence time and the number of bounces. The hydrodynamic criterion was more consistent in representing our data on coalescence time.

Methodology for the thermoelastic stress analysis of complex biomimetic structures: An alligator mandible case study

Biomimetic designs that take inspiration from natural structures provide a unique approach to identifying innovative solutions to engineering problems. The experimental analysis of such structures, however, can be difficult due to complex, three-dimensional geometric features. This study presents a methodology for the analysis of complex biomimetic structures using thermoelastic stress analysis (TSA) illustrated through an alligator mandible case study. This structure has evolved to become optimal for its function and environment which has resulted in unique and intricate features. An additively manufactured alligator mandible structure was experimentally analysed using TSA under bending load conditions and compared to a finite element (FE) solution. TSA was found to be a suitable method for the qualitative and quantitative analysis of the complex biomimetic structure which correlated well with the FE model. This study demonstrates the accuracy of TSA for the assessment of biomimetic designs with unique, arbitrary geometric features that can be utilised for future nature-inspired engineering applications.

Experimental and theoretical modeling of droplet break-up of W/O emulsion flow in ESPs

The behavior of water-in-oil emulsions flow within Electrical Submersible Pumps (ESPs) is of significant interest in the oil and gas industry due to its complex rheological characteristics, which are influenced by operational parameters and the chemical properties of both phases. Operational parameters such as dispersed phase fraction, temperature, flow rate, and pump design were investigated experimentally in this work. Improved semi-empirical models for mean and maximum droplet diameter estimation were also proposed. Through extensive experimentation and statistical analysis, this study reveals that smaller droplets form with increasing dispersed phase fraction and the flow geometry significantly affects droplet breakage intensity. The proposed models integrate the dispersed phase fraction, dimensionless flow rate, specific speed, and energy dissipation rate, exhibiting commendable alignment with experimental findings. This not only helps predict effective viscosity but offers valuable insights for further analyses, particularly regarding catastrophic phase inversion (CPI) prediction. These aspects have significant importance in the oil and gas industry and can enable the optimization of production systems and processing facilities.

Unravelling the multiple effects of H2O on the NH3-SCR over Mn2Cu1Al1Ox-LDO by transient kinetics and in situ DRIFTS

Understanding detrimental effects of water in the low-temperature NH3-SCR is very important for advancing the design of novel catalytic materials. Herein, the effects of 5 vol% H2O on the performance of NH3-SCR over Mn2Cu1Al1Ox-LDO were investigated through steady-state and transient kinetic analysis of step-gas switching experiments, in-situ DRIFTS and 15NO-SSITKA-DRIFTS operando. Water exhibited a significant negative activity effect at T<180 °C. Slightly positive activity (200–300 °C) and N2-selectvity (120–300 °C) effects were observed due to suppression of NH3 oxidation and NH4NO3 decomposition to N2O. The decline in activity at 140 °C by ∼ 45 % in the presence of water was found to be related to the decrease of the site activity (k) and not of surface coverage (θ) of active species formed in the NH3-SCR reaction paths of N2/N2O formation. An increase in the concentration of inactive NOx-s might also contribute to the inhibitive effect of water.

Optimizing magnetometers arrays and analysis pipelines for multivariate pattern analysis

BackgroundMultivariate pattern analysis (MVPA) has proven an excellent tool in cognitive neuroscience. It also holds a strong promise when applied to optically-pumped magnetometer-based magnetoencephalography. New methodTo optimize OPM-MEG systems for MVPA experiments this study examines data from a conventional MEG magnetometer array, focusing on appropriate noise reduction techniques for magnetometers. We determined the least required number of sensors needed for robust MVPA for image categorization experiments. ResultsWe found that the use of signal space separation (SSS) without a proper regularization significantly lowered the classification accuracy considering a sub-array of 102 magnetometers or a sub-array of 204 gradiometers. We also found that classification accuracy did not improve when going beyond 30 sensors irrespective of whether SSS has been applied. Comparison with existing methodsThe power spectra of data filtered with SSS has a substantially higher noise floor that data cleaned with SSP or HFC. Consequently, MVPA decoding results obtained from the SSS-filtered data are significantly lower compared to all other methods employed. ConclusionsWhen designing MEG system based on SQUID magnetometers optimized for multivariate analysis for image categorization experiments, about 30 magnetometers are sufficient. We advise against applying SSS filters without a proper regularization to data from MEG and OPM systems prior to performing MVPA as this method, albeit reducing low-frequency external noise contributions, also introduces an increase in broadband noise. We recommend employing noise reduction techniques that either decrease or maintain the noise floor of the data like signal-space projection, homogeneous field correction and gradient noise reduction.

Improving rigor and reproducibility in western blot experiments with the blotRig analysis

Western blot is a popular biomolecular analysis method for measuring the relative quantities of independent proteins in complex biological samples. However, variability in quantitative western blot data analysis poses a challenge in designing reproducible experiments. The lack of rigorous quantitative approaches in current western blot statistical methodology may result in irreproducible inferences. Here we describe best practices for the design and analysis of western blot experiments, with examples and demonstrations of how different analytical approaches can lead to widely varying outcomes. To facilitate best practices, we have developed the blotRig tool for designing and analyzing western blot experiments to improve their rigor and reproducibility. The blotRig application includes functions for counterbalancing experimental design by lane position, batch management across gels, and analytics with covariates and random effects.

Cooling effect and parameter analysis of applying heat insulation layer to tunnel regionalization in construction period based on geothermal level

The construction of high geothermal tunnels presents significant difficulties due to the abnormal rock temperature gradients, including designing a reasonable and cost-effective insulation layer as well as effective cooling measures. In this study, the rock temperature distribution, environmental temperature, and lining surface temperature of the tunnel during the construction period were analyzed through field surveys. A numerical simulation model considering ventilation and heat transfer dynamics was established based on the geothermal measurements and construction characteristics of this tunnel. After validating the 3D numerical model, the effects of installing heat insulation layers according to geothermal levels on the tunnel temperature field control were investigated. Additionally, the impacts of different insulation layer thermal conductivities (λi), ventilation air volume (Wa), and duct thermal conductivities (λd) were analyzed. The results indicate: (1) The comparison of temperature fields in tunnels with insulation layers, which is applied in the range of the rock temperature above 50 °C and without insulation layers was made. The temperature near the excavation face (TAm-1) decreases by up to 0.3% (0.5 °C), tunnel environment temperature with insulation layer applied (TAm-2) decreases by up to 4.2% (2.1 °C), the secondary lining temperature (TSec-lining) decreases by up to 10.5% (4.6 °C), and the wind temperature of air duct outlet (TAir-duct) decreases by up to 0.7% (0.5 °C). (2) The length of the insulation layer increases to the full length of the tunnel, TAm-1 continues to decline by only 0.4°C, TAm-2 by 0.5 °C, TSec-lining by 0.9 °C, and TAir-duct by 0.1 °C, which shows that it is the most economical and reasonable to apply the insulation layer only in the tunnel area where the rock temperature is higher than 50 °C. (3) As λi increases, both the tunnel environment and secondary lining temperatures exhibit linear increases, while increasing Wa and λi cause quadratic decreases and increases in tunnel temperature field parameters, respectively. (4) Range analysis of orthogonal experiments reveals that for tunnel temperature field impact level. For TAm-1, the significance order is Wa >λd >λi. And for TAm-2 and TSec-lining, the significance order is Wa >λi >λd, which can provide the more economical scheme for the insulation layer design and cooling schemes in the high ground temperature tunnel.