Single Process Research Articles

The enhancement of heterobimetallic MOFs on the pyrolysis and laser ignition of FOX-7

The hydrothermal approach had been used to synthesize two new heterobimetallic Metal Organic Frameworks (MOFs), Ba4Pb4(CH3CO2)8[(CH6CO2)4Pb](CH3CO2)4 (PbBa-MOF) and Ba2Ni(CO2H)6(OH2)4 (NiBa-MOF), their structure and surface topography were then examined with XRD and SEM. By using the TG-DSC and TG-FTIR-MS methods, the pyrolytic decomposition properties of MOFs and their catalytic activities on the 1,1-diamino-2,2-dintroethene (FOX-7) pyrolysis were investigated. The PbBa-MOF has a single thermal decomposition process with a high thermal decomposition temperature, while NiBa-MOF has a three-stage thermal decomposition process initiated from a lower temperature. Furthermore, the thermolysis peak temperature of the FOX-7/PbBa-MOF and FOX-7/NiBa-MOF mixture has a great decrease by 24.2 °C and 27.4 °C compared with the FOX-7. However, the low pyrolysis peak temperature and the pyrolysis activation energy (Ea) are almost unchanged. The selective high temperature catalytic effect of the MOFs on FOX-7 results from the activation of -NH2 in the high temperature pyrolytic decomposition of FOX-7 by the metallic ions of the MOFs. This thermal catalytic property indicates that MOFs can promote the pyrolytic decomposition of FOX-7 while ensuring the safety requirements for the compatibility of energetic mixtures in the preparation of propellants. The relationship between the features of pyrolytic decomposition and laser ignition was finally covered and defined. The two MOFs decreased the minimum ignition energy and ignition delay time of the FOX-7. Novel MOFs combustion catalyst may strengthen ignition and combustion features of the high-energy and low-sensitivity solid propellants containing FOX-7.

Towards sequential sensor placements on a wind farm to maximize lifetime energy and profit

The optimal design of a wind farm which maximizes energy production depends on the spatially variable wind flow field. However, due to the complexity associated with modeling atmospheric winds, especially in the presence of complex terrain, the wind field is inherently uncertain. Uncertainty in the wind field during the design stage reduces the likelihood that the constructed wind farm achieves maximum energy production for a given number of turbines. As such, contemporary wind farms are designed through a two step process. First, experimental data collected from simultaneously constructed meteorological towers are used, along with simplified engineering flow models, to estimate the flow field. Then, the estimated flow field is used to place wind turbines to maximize an objective function, such as wind farm energy production. To increase wind farm energy production and reduce its uncertainty, we propose a farm design methodology that combines both the sensor placement and wind turbine location selection steps into a single sequential decision-making process. Future sensor placements sequentially leverage information gained from previous ones. Rather than placing sensors to attempt to reduce wind field uncertainty, we select sensor locations to maximize wind farm profit. Using profit as the objective function balances the increased revenue, from the increased energy production associated with improved wind field knowledge, against the higher costs from additional sensors. In this proof-of-concept study, we use idealized numerical case studies to demonstrate that sequential wind field sensor placement, compared to concurrent placement, improves the robustness of the resulting wind farm design to imperfect initial knowledge of the wind field. The numerical results suggest a wind farm annual energy output (lifetime profit) increase of approximately 6.55% (16.78%), equaling roughly 0.7 GWh/year (0.35 million USD) per turbine, compared to a typical, two-step wind farm design process which first places sensors concurrently then designs the farm thereafter. Our results also indicate that using a far-sighted sequential method as proposed in this paper outperforms standard metrics, such as entropy, that solely focus on wind field uncertainty minimization. These proof-of-concept findings suggest that future research should be dedicated to improving the wind farm design process through sequential decision-making under uncertainty.

Combined ozone, photo, and electrocoagulation technologies-An innovative technique for treatment of distillery industrial wastewater

Electrocoagulation with ozone and photo is a hybrid electrochemical and AOP techniques used to treat wastewater and industrial effluent. In the present study, the effects of combining O3, UV, and EC processes on color removal as well as the related COD removal and EEC from the treatment of DIW were assessed. The results showed that, compared to other hybrid processes like O3/EC, UV/EC, UV/O3, and single processes of EC, O3, and UV, the combined process of O3/UV/EC is significantly more effective for treating DIW in terms of COD removal (98.99%) and complete color removal with a required EEC of 9.7 kWhr m-3. Number of process variables, including reaction time (1 to 5 hr), O3 (0.8 to 4 g L-1), UV (8 to 32 W), current density (0.08 to 0.23 A dm-2), pH (1 to 11), COD (1000 to 6000 mg L-1), inter-electrode distance (0.75 to 3.75 cm), and combination of electrodes were studied to analyze how they affected. The optimum operating circumstances underwent testing and shown outstanding effectiveness in eliminating the COD and determination of EEC from DIW. Overall, it was clear from the results that combined treatment approaches could be more effective in removing the pollutant successfully from DIW.

Optimization of energy recovery efficiency from sweet sorghum stems by ethanol and methane fermentation processes coupling

ABSTRACTTaken separately, a single sweet sorghum stem bioconversion process for bioethanol and biomethane production only leads to a partial conversion of organic matter. The direct fermentation of crushed whole stem coupled with the methanization of the subsequent solid residues in a two-stage process was experimented to improve energy bioconversion yield, efficiency, and profitability. The raw stalk calorific value was 17,144.17 kJ/kg DM. Fermentation step performed using Saccharomyces cerevisiae resulted in a bioconversion yield of 261.18 g Eth/kg DM, i.e. an energy recovery efficiency of 6921.27 kJ/kg DM. The methanogenic potentials were 279 and 256 LCH4/kg DM, respectively, for raw stem and fermentation residues, i.e. energy yields of 10,013.31 and 9187.84 kJ/kg DM, respectively. Coupling processes have significantly increased yield and made it possible to reach 13,309.57 kJ/kg DM, i.e. 77.63% of raw stem energy recovery yield, compared to 40.37% and 58.40%, respectively, for single fermentation and methanization processes.

Secondary motor integration as a final arbiter in sensorimotor decision-making.

Sensorimotor decision-making is believed to involve a process of accumulating sensory evidence over time. While current theories posit a single accumulation process prior to planning an overt motor response, here, we propose an active role of motor processes in decision formation via a secondary leaky motor accumulation stage. The motor leak adapts the "memory" with which this secondary accumulator reintegrates the primary accumulated sensory evidence, thus adjusting the temporal smoothing in the motor evidence and, correspondingly, the lag between the primary and motor accumulators. We compare this framework against different single accumulator variants using formal model comparison, fitting choice, and response times in a task where human observers made categorical decisions about a noisy sequence of images, under different speed-accuracy trade-off instructions. We show that, rather than boundary adjustments (controlling the amount of evidence accumulated for decision commitment), adjustment of the leak in the secondary motor accumulator provides the better description of behavior across conditions. Importantly, we derive neural correlates of these 2 integration processes from electroencephalography data recorded during the same task and show that these neural correlates adhere to the neural response profiles predicted by the model. This framework thus provides a neurobiologically plausible description of sensorimotor decision-making that captures emerging evidence of the active role of motor processes in choice behavior.

All‐In‐One Detection, Removal and Recovery of Hg2+ in Industrial Wastewater with Plasmonic Schottky Heterostructures

AbstractThe effective governance of Hg2+ in environmental wastewater is of profound significance to deal with the global pollution issues. However, the present methodologies usually only focused on a single function of either detection or removal, which encounters severe secondary pollution and cumbersome operation cost, while the integration of Hg2+ detection, removal, and recovery in one process is barely realized. In this study, an All‐In‐One photoelectrochemical system is built combining the detection, removal, and recovery of Hg2+ pollutant in a single process, by ingeniously developing a fundamental principle, namely alloying‐induced plasmonic quenching mechanism in Schottky heterostructures. Briefly, the high‐efficiency removal and recovery of Hg2+ in wastewater is realized via the favorable alloying of Hg in Ag nanoparticles that well‐dispersed on the free‐standing WO3 nanoplate networks. The formation of Ag–Hg alloy future leads to a remarkable plasmonic quenching effect of the Ag nanoparticles, which is used to modulate the photoelectrochemical singles to realize the high‐precision detection. Through this ingenious design, an ultralow Hg2+ detection limit of 0.296 nm is achieved with a broad detection range up to 12.5 µm, and meanwhile realize a removal/recovery rate of 100% in single Hg2+ solution and 97 ± 2% in industrial wastewater with multiple contamination ions. The detection and removal/recovery performance parameters reported in the study are much better as compared to the recently reported single function detection or removal/recovery systems. This work opens a fresh avenue in tackling the problem of heavy metal pollution using plasmonic Schottky heterostructure based All‐In‐One systems.

Expressive recall and recognition as complementary measures to assess novel word learning ability in aphasia

Novel word learning ability has been associated with language treatment outcomes in people with aphasia (PWA), and its assessment could inform prognosis and rehabilitation. We used a brief experimental task to examine novel word learning in PWA, determine the value of phonological cueing in assessing learning outcomes, and identify factors that modulate learning ability. Twelve PWA and nineteen healthy controls completed the task, and recall and recognition tests of learning ability. Most PWA showed comparable learning outcomes to those of the healthy controls. Learning assessed via expressive recall was more clearly evidenced with phonological cues. Better single word processing abilities and phonological short-term memory and higher integrity of the left inferior frontal gyrus were related to better learning performance. Brief learning tasks like this one are clinically feasible and hold promise as screening tools of verbal learning in PWA once validated and evaluated for their capacity to predict treatment outcomes.

Assessing the Productivity of Forest Harvesting Systems Using a Combination of Forestry Machines in Steep Terrain

Despite similarly steep terrain, the productivity of forest harvesting operations in Japan is lower than in Central Europe. Harvesting systems in Japan are typically characterized by the four production processes of felling, yarding, processing, and forwarding, whereas in Central Europe they have mostly been reduced to just two through the use of a PTY (Processor Tower Yarder). This study investigated the number of production processes as a reason for the relatively lower productivity of forest harvesting in Japan using the Combined Machine Productivity (CMP) and Combined Labor Productivity (CLP) indices. The CMP and CLP were 1.81 m3/h and 0.45 m3/worker/h, respectively, for a parallel production model based on a typical Japanese forest harvesting system in Japan. The CMP and CLP values were improved to 2.51 m3/h and 0.63 m3/worker/h, respectively, when the forwarding process was removed from the model. The CMP and CLP values were further improved to 3.04 m3/h and 0.76 m3/worker/h, respectively, when yarding and processing were integrated into a single process. Reducing the number of the production processes can therefore improve the productivity of forest harvesting operations in Japan.

Integration of Multivariate Statistical Control Chart and Machine Learning to Identify the Abnormal Process Parameters for Polylactide with Glass Fiber Composites in Injection Molding; Part I: The Processing Parameter Optimization for Multiple Qualities of Polylactide/Glass Fiber Composites in Injection Molding.

This paper discusses the mixing of polylactide (PLA) and glass fiber which use injection molding to produce a functional composite material with glass fiber properties. The injection molding process explores the influence of glass fiber ratio, melt temperature, injection speed, packing pressure, packing time and cooling time on the mechanical properties of composite. Using the orthogonal table planning experiment of the Taguchi method, the optimal parameter level combination of a single quality process is obtained through main effect analysis (MEA) and Analysis of variance (ANOVA). Then, the optimal parameter level combination of multiple qualities is obtained through principal component analysis (PCA) and data envelopment analysis (DEA), respectively. It is observed that if all the quality characteristics of tensile strength, hardness, impact strength and bending strength are considered at the same time, the optimal process conditions are glass fiber addition 20 wt %, melt temperature 185 °C, injection speed 80 mm/s, holding pressure 60 MPa, holding time 1 s and cooling time 15 s, and the corresponding mechanical properties are tensile strength 95.04 MPa, hardness 86.52 Shore D, impact strength 4.4408 J/cm2, bending strength 119.89 MPa. This study effectively enhances multiple qualities of PLA/GF composite.

Tailoring microstructure and strength through selective remelting in laser powder bed fusion

Additive manufacturing provides new opportunities to manipulate local microstructure to enable strengthening pathways for austenitic stainless steels. Laser beam powder bed fusion techniques, however, are limited by their narrow process window, as compared to other additive manufacturing techniques. In this work, the use of layer-wise remelting is explored to expand the available process window in laser powder bed fusion to manipulate the microstructure and increase strength while minimizing porosity. Several single melt process conditions are considered for 316L stainless steel along with additional low energy and high energy remelts to evaluate the effect on grain morphology, texture, porosity, and hardness. Results demonstrate remelting as an effective approach to tune grain size and texture to achieve high hardness while reducing the overall porosity. While the data suggest that the optimal single melt process set results in the lowest porosity, remelting provides a pathway to reduce porosity for non-optimal process parameters, minimize grain growth, and increase strength.

Cadmium and Arsenic Interactions During Co-adsorption onto Goethite

Cadmium (Cd) and arsenic (As) are commonly co-adsorbed onto iron oxides in the soil environment, especially in south China. This study aimed to elucidate the regulatory mechanisms in determining the As(Ⅴ)-Cd(Ⅱ) interactions on a goethite interface after excluding pH interference. At pH 6.0, the results obtained illustrated that As(Ⅴ) and Cd(Ⅱ) adsorbed onto goethite obeyed the pseudo-second-order kinetic model, and the adsorption processes were mainly chemical adsorption. Furthermore, As(Ⅴ) adsorbed onto goethite were mainly inner ring adsorption and monolayer adsorption both in the single adsorption process and in co-adsorption processes with Cd(Ⅱ). For comparison, Cd(Ⅱ) adsorbed onto goethite also demonstrated inner ring adsorption and monolayer adsorption during single adsorption, and As(Ⅴ)-Cd(Ⅱ) co-adsorption were transformed to outer ring adsorption and multilayer adsorption processes. Through analysis by Zeta potential, X-ray diffraction, and X-ray photoelectron spectroscopy, electrostatic adsorption and formation of ternary complexes (Fe-As-Cd) were proven to be the critical mechanisms in determining the interactions between As(Ⅴ) and Cd(Ⅱ) during their co-adsorption processes. The results obtained in this study should help us to further understand the micro-chemical interaction processes of heavy metals on the soil environment.

Decoherence effects in reactor and Gallium neutrino oscillation experiments: a QFT approach

We adopt the quantum field theoretical method to calculate the amplitude and event rate for a neutrino oscillation experiment, considering neutrino production, propagation and detection as a single process. This method allows to take into account decoherence effects in the transition amplitude induced by the quantum mechanical uncertainties of all particles involved in the process. We extend the method to include coherence loss due to interactions with the environment, similar to collisional line broadening. In addition to generic decoherence induced at the amplitude level, the formalism allows to include, in a straightforward way, additional damping effects related to phase-space integrals over momenta of unobserved particles as well as other classical averaging effects. We apply this method to neutrino oscillation searches at reactor and Gallium experiments and confirm that quantum decoherence is many orders of magnitudes smaller than classical averaging effects and therefore unobservable. The method used here can be applied with minimal modifications also to other types of oscillation experiments, e.g., accelerator based beam experiments.

Full‐Hexacyanometallate Aqueous Redox Flow Batteries Exceeding 1.5 V in an Aqueous Solution

AbstractAqueous redox flow batteries (RFBs) have attracted significant attention as energy storage systems by virtue of their inexpensive nature and long‐lasting features. Although all‐vanadium RFBs exhibit long lifetimes, the cost of vanadium resources fluctuates considerably, and is generally expensive. Iron–chromium RFBs take advantage of utilizing a low‐cost and large abundance of iron and chromite ore; however, the redox chemistry of CrII/III generally involves strong Jahn–Teller effects. Herein, this work introduces a new Cr‐based negolyte coordinated with strong‐field ligands capable of mitigating strong Jahn–Teller effects, thereby facilitating low redox potential, high stability, and rapid kinetics. The balanced full‐cell configuration features a stable lifetime of 500 cycles with energy density of 14 Wh L−1. With an excessive posolyte, the full‐cell can attain a high energy density of 38.6 Wh L−1 as a single electron redox process. Consequently, the proposed system opens new avenues for the development of high‐performance RFBs.

Advantages of Injection Mold with Hybrid Process of Metal Powder Bed Fusion and Subtractive Process

This paper focuses on the hybrid process combining metal additive manufacturing (AM) and subtractive processing developed for application to injection molds. The basic concept is a combination of laser powder bed fusion of metal powder and subtractive processing. This process is characterized by alternating buildup and milling processes. Even the inner surface of deep grooves, which conventionally required electrical discharge machining, can be machined with small-diameter tools with a short flute length. Therefore, molds with complex shapes that previously required electrical discharge machining can be manufactured in a single process. Moreover, a dimensional accuracy and surface roughness of levels equal to those achieved by machining with the machining center can be ensured. In the hybrid process, it is necessary to minimize the surplus solidified area (which is the area milled by the small-diameter tool). Therefore, the formation mechanism of the surplus solidified region is verified. It is shown that the power distribution of the laser beam significantly affects the size (width and depth) and density distribution of the excessively solidified region. In addition, the effective value of metal AM mold is introduced. The 3D cooling circuit improves the efficiency of the injection molding process. If the temperature balance between the cavity side and core side is achieved, the distortion of the molded product would be suppressed. If the cooling effect is promoted, the molding cycle would be shortened substantially. Second, the effect of the gas vent function by a permeable structure is explained through actual examples. The effect of the gas vent function by the permeable structure is explained. It is indicated that stable molding can be achieved. In addition, the appearance defects of molded products can be reduced when the air inside the cavity is exhausted sufficiently from the mold through the permeable structure.

Phylogenetic congruence, conflict and consilience between molecular and morphological data

Morphology and molecules are important data sources for estimating evolutionary relationships. Modern studies often utilise morphological and molecular partitions alongside each other in combined analyses. However, the effect of combining phenomic and genomic partitions is unclear. This is exacerbated by their size imbalance, and conflict over the efficacy of different inference methods when using morphological characters. To systematically address the effect of topological incongruence, size imbalance, and tree inference methods, we conduct a meta-analysis of 32 combined (molecular + morphology) datasets across metazoa. Our results reveal that morphological-molecular topological incongruence is pervasive: these data partitions yield very different trees, irrespective of which method is used for morphology inference. Analysis of the combined data often yields unique trees that are not sampled by either partition individually, even with the inclusion of relatively small quantities of morphological characters. Differences between morphology inference methods in terms of resolution and congruence largely relate to consensus methods. Furthermore, stepping stone Bayes factor analyses reveal that morphological and molecular partitions are not consistently combinable, i.e. data partitions are not always best explained under a single evolutionary process. In light of these results, we advise that the congruence between morphological and molecular data partitions needs to be considered in combined analyses. Nonetheless, our results reveal that, for most datasets, morphology and molecules can, and should, be combined in order to best estimate evolutionary history and reveal hidden support for novel relationships. Studies that analyse only phenomic or genomic data in isolation are unlikely to provide the full evolutionary picture.

What controls carbon sequestration in plants under which conditions?

Photosynthetic organisms use photosynthesis to harvest sunlight and convert the solar energy into chemical energy, which is then used to reduce atmospheric carbon dioxide into organic molecules. This process forms the basis of all life on Earth, and stands at the beginning of the food chain which feeds the world population. Not surprisingly, many research efforts are currently ongoing aiming at improving growth and product yield of photosynthetic organisms, and several of these activities directly target the photosynthetic pathways. Metabolic Control Analysis (MCA) shows that, in general, the control over a metabolic flux, such as carbon fixation, is distributed among several steps and highly dependent on the external conditions. Therefore, the concept of a single ‘rate-limiting’ step is hardly ever applicable, and as a consequence, any strategy relying on improving a single molecular process in a complex metabolic system is bound to fail to yield the expected results. In photosynthesis, reports on which processes exert the highest control over carbon fixation are contradictory. This refers to both the photosynthetic ‘light’ reactions harvesting photons and the ’dark’ reactions of the Calvin–Benson–Bassham Cycle (CBB cycle). Here, we employ a recently developed mathematical model, which describes photosynthesis as an interacting supply–demand system, to systematically study how external conditions affect the control over carbon fixation fluxes.

UV polymerization fabrication method for polymer composite based optical fiber sensors

Optical fiber (OF) sensors are critical optical devices with excellent sensing capabilities and the capacity to operate in remote and hostile environments. However, integrating functional materials and micro/nanostructures into the optical fiber systems for specific sensing applications has limitations of compatibility, readiness, poor control, robustness, and cost-effectiveness. Herein, we have demonstrated the fabrication and integration of stimuli-responsive optical fiber probe sensors using a novel, low-cost, and facile 3D printing process. Thermal stimulus–response of thermochromic pigment micro-powders was integrated with optical fibers by incorporating them into ultraviolet-sensitive transparent polymer resins and then printed via a single droplet 3D printing process. Hence, the thermally active polymer composite fibers were grown (additively manufactured) on top of the commercial optical fiber tips. Then, the thermal response was studied within the temperature range of (25–35 °C) and (25–31 °C) for unicolor and dual color pigment powders-based fiber-tip sensors, respectively. The unicolor (with color to colorless transition) and dual color (with color to color transition) powders-based sensors exhibited substantial variations in transmission and reflection spectra by reversibly increasing and decreasing temperatures. The sensitivities were calculated from the transmission spectra where average change in transmission spectra was recorded as 3.5% with every 1 °C for blue, 3% for red and 1% for orange-yellow thermochromic powders based optical fiber tip sensors. Our fabricated sensors are cost-effective, reusable, and flexible in terms of materials and process parameters. Thus, the fabrication process can potentially develop transparent and tunable thermochromic sensors for remote sensing with a much simpler manufacturing process compared to conventional and other 3D printing processes for optical fiber sensors. Moreover, this process can integrate micro/nanostructures as patterns on the optical fiber tips to increase sensitivity. The developed sensors may be employed as remote temperature sensors in biomedical and healthcare applications.

Mechanism and treatment of cell death in Alzheimer's disease

With 60 to 80% of cases, Alzheimer's disease (AD) is the primary trigger of dementia around the globe. The prevalence of people aged 65-69 years increased from 1% to about 30% of people aged 85 years, resulting in more than 50 million affected individuals globally. The AD in the formation of amyloid, the tau protein distribution, the interaction between amyloid and tau protein, clinical symptoms, the genetic background and so on various aspects are heterogeneity exists. Therefore, there is no single pathological process or mechanism of action that can explain why people develop AD. The prevalence of Alzheimer's disease is one of the largest global public health issues today. There have been many different therapy modalities investigated over time. But there is still no cure, and all that can be done for AD is to prevent and delay its progression. Current drug treatments are intended only to alleviate symptoms, not cure the root cause. Based on the universalization and decreasing age of AD, it is particularly significant to study the causes and pathogenesis of AD and how to prevent and treat it. This paper introduces the main stages of the process of AD, introduces two hypotheses -- tau hypothesis and amyloid interpretation，and the role of RNA splicing in this process is summarized. In addition, in order to provide more research ideas, the author describes the current treatment options for AD, from the risk factors that may cause AD to the latest specific treatments. The treatment approach suggests that both at-risk patients and those without underlying diseases make early lifestyle and dietary adjustments and gradually move towards a healthy lifestyle in order to reduce the incidence of Alzheimer's and the financial burden on families and society. This is in addition to early drug treatment to lessen the suffering and life experience of Alzheimer's patients.

Investigations of turbulence influence on pressure swing adsorption process for CO2 capture by computational mass transfer

Capture, utilization, and storage of CO2 (CCUS) is an effective way to achieve a low carbon and sustainable future, and PSA is one of the CO2 separation technologies that has been widely studied due to its advantages of simple equipment and low energy consumption. The uncertain flow state of the fluid can indeed have an impact on accurate modeling during the research process of capturing CO2 with PSA. In this study, we compare the two-equation turbulent (TET) model based on the computational mass transfer method (Yu and Yuan, 2017 [1]) with the laminar model commonly assumed in previous studies, to investigate the dynamic PSA process involving multi-steps of carbon dioxide separation in a single-column, with the purpose of exploring the differences caused by selecting different flow state models during the modeling process. The study utilizes the two models to simulate a single column PSA process, which consists of adsorption, vacuuming, purging, and pressurization to capture CO2. The simulation results are compared with experimental data, and compared to the laminar model, the TET model is found to be more in line with the actual process. The effect of turbulent diffusion on the concentration and velocity distributions is also investigated by comparing the two models, and the radial distribution becomes more uniform as the turbulent diffusion is taken into account in the TET model. The intensity of turbulent diffusion is analyzed for each step, and the pressurization stage shows intense turbulent characteristics that will impact the whole process.

Cavity reverse expansion considering elastoplastic unloading and application in cast-in-situ bored piles

The construction process of a cast-in-situ bored pile is too complicated to be described by the cavity expansion theory with a single process. An exact unified semi-analytical solution for both cylindrical and spherical cavities reverse expansion after unloading in drained soil is developed. The non-associated Mohr-Coulomb model and definition of logarithmic strain are adopted in the reverse plastic zone. This model can be used to solve the stress and displacement fields of the soil around a bored pile along both the horizontal and depth directions. Parametric analysis shows that the effect of the unloading phase does not change the ultimate pressure of cavity reverse expansion compared with in situ expansion. The cavity cannot re-expand to its initial radius even though the cavity pressure reloads to the initial value. The increase of internal friction angle, cohesion, and Young's modulus has a positive effect on radius recovery, while the dilatancy angle has a negative effect. A simulation of the construction process of cast-in-situ bored piles is presented, where the role of boring, mud wall protection, and concrete placement is defined. An example that describes the stress and displacement fields around a pile shows that the total radial displacement of soil around the pile is dominated by contraction displacement. And it is closely related to depth and horizontal distance. The results of both parameter analysis and example analysis demonstrate that a low reverse cavity pressure corresponds to a stress-reduction area surrounding the cavity.