Survival Analysis Using Cox Proportional Hazards Regression for Pile Bridge Piles Under Wet Service Conditions

This paper studies the deterioration of bridge substructures utilizing the Long-Term Bridge Performance(LTBP)Program InfoBridge^(TM)and develops a survival model using Cox proportional hazards regression.The survival anal­ysis is based on the National Bridge Inventory(NBI)dataset.The study calculates the survival rate of reinforced and prestressed concrete piles on bridges under marine conditions over a 29-year span(from 1992 to 2020).The state of Maryland is the primary focus of this study,with data from three neighboring regions,the District of Columbia,Vir­ginia,and Delaware to expand the sample size.The data obtained from the National Bridge Inventory are condensed and filtered to acquire the most relevant information for model development.The Cox proportional hazards regres­sion is applied to the condensed NBI data with six parameters:Age,ADT,ADTT,number of spans,span length,and structural length.Two survival models are generated for the bridge substructures:Reinforced and prestressed concrete piles in Maryland and reinforced and prestressed concrete piles in wet service conditions in the District of Columbia,Maryland,Delaware,and Virginia.Results from the Cox proportional hazards regression are used to construct Markov chains to demonstrate the sequence of the deterioration of bridge substructures.The Markov chains can be used as a tool to assist in the prediction and decision-making for repair,rehabilitation,and replacement of bridge piles.Based on the numerical model,the Pile Assessment Matrix Program(PAM)is developed to facilitate the assessment and main­tenance of current bridge structures.The program integrates the NBI database with the inspection and research reports from various states’department of transportation,to serve as a tool for condition state simulation based on mainte­nance or rehabilitation strategies.

Probabilistic prediction of expected ground condition and construction time and costs in road tunnels

Ground condition and construction （excavation and support） time and costs are the key factors in decision-making during planning and design phases of a tunnel project. An innovative methodology for probabilistic estimation of ground condition and construction time and costs is proposed, which is an integration of the ground prediction approach based on Markov process, and the time and cost variance analysis based on Monte-Carlo （MC） simulation. The former provides the probabilistic description of ground classification along tunnel alignment according to the geological information revealed from geological profile and boreholes. The latter provides the probabilistic description of the expected construction time and costs for each operation according to the survey feedbacks from experts. Then an engineering application to Hamro tunnel is presented to demonstrate how the ground condition and the construction time and costs are estimated in a probabilistic way. In most items, in order to estimate the data needed for this methodology, a number of questionnaires are distributed among the tunneling experts and finally the mean values of the respondents are applied. These facilitate both the owners and the contractors to be aware of the risk that they should carry before construction, and are useful for both tendering and bidding.

Prediction of Interbeds Intercalated into Complex Heterogeneous Reservoirs at a High Water Cut Stage

The occurrence of interbeds in thick oil formations is one of the main reasons that cause the difference of remaining oil distribution. A quantitative method for predicting interbeds was proposed and the sedimentary origin and division criterion were demonstrated. The distribution of interbeds in different types of sedimentary sand bodies were predicted and analyzed by combining the theory of sedimentology and reservoir bed architectural-element analysis. The interbeds in a single well were recognized from high resolution well logs, and inter-well interbeds were predicted by using the methods of cyclothem correlation, physical properties trtmcation, and conditional simulation. Finally a 3-D model of interbed was built. Application to the Gudao Oilfield was successful.

Numerical simulation of hydrodynamic characteristics during the diversion closure in a horizontal tunnel

Based on water inrush accident of 1841 working face of Desheng Coal Mine in Wu'an, Hebei province, China, an evaluation model of hydrodynamic characteristics of the project is set up and simulated using Matlab. It is assumed that the pipe flow would transform into seepage flow when the aggregates are plugged into the water inrush channel and the seepage flow would disappear along with grouting process. The simulation results show that the flow velocity will increase with an increase in height of aggregates accumulation body during the aggregates filling process; the maximum seepage velocity occurs on the top of plugging zone; and the water flow decreases with increasing plugging height of water inrush channel. Finally, the field construction results show that the water inrush channel can be plugged effectively by the compacted body prepared with aggregate and cement slurry.

Reactive mesoporous silica nanoparticles loaded with limonene for improving physical and mental health of mice at simulated microgravity condition

Astronauts are under high stress for a long time because of the microgravity condition,which leads to anxiety,affects their learning and memory abilities,and seriously impairs the health of astronauts.Aromatherapy can improve the physical and mental health of astronauts in a way that moisturizes them softly and silently.However,the strong volatility of fragrances and inconvenience of aroma treatment greatly limit their application in the field of spaceflight.In this study,reactive mesoporous silica nanoparticles were prepared to encapsulate and slowly release limonene.The limonene loaded nanoparticles were named limonene@mesoporous silica nanoparticles-cyanuric chloride(LE@MSNs-CYC).LE@MSNs-CYC were then applied to wallpaper to improve the convenience of aromatherapy.LE@MSNs-CYC could chemically react with the wallpaper,thus firmly adsorbed on the wallpaper.In the following,the mice were treated with hindlimb unloading(HU)to simulate a microgravity environment.The results showed that 28-day HU led to an increase in the level of anxiety and declines in learning,memory,and physical health in mice.LE@MSNs-CYC showed significant relief effects on anxiety,learning,memory,and physical health of HU treated mice.Subsequently,the molecular mechanisms were explored by hypothalamic-pituitary-adrenal axis related hormones,immune-related cytokines,learning,and memory-related neurotransmitters and proteins.

Computational fluid dynamics simulation of friction stir welding:A comparative study on different frictional boundary conditions

Numerical simulation based on computational fluid dynamics （CFD） is a useful approach for quantitatively investigating the underlying thermal-mechanical conditions during FSW, such as temperature field and material deformation field. One of the critical issues in CFD simulation of FSW is the use of the frictional boundary condition, which represents the friction between the welding tool and the workpiece in the numerical models. In this study, three-dimensional numerical simulation is conducted to analyze the heat transfer and plastic deformation behaviors during the FSW of AA2024. For comparison purposes, both the boundary velocity （BV） models and the boundary shear stress （BSS） models are employed in order to assess their performances in predicting the temperature and material deformation in FSW. It is interesting to note that different boundary conditions yield similar predictions on temperature, but quite different predictions on material deformation. The numerical predictions are compared with the experimental results. The predicted deformation zone geometry by the BSS model is consistent with the experimental results while there is large difference between the predictions by the BV models and the experimental measurements. The fact that the BSS model yields more reasonable predictions on the deformation zone geometry is attributed to its capacity to automatically adjust the contact state at the tool/workpiece interface. Based on the favorable predictions on both the temperature field and the material deformation field, the BSS model is suggested to have a better performance in numerical simulation of FSW than the BV model.

Quantitative Integration of High-Resolution Hydrogeophysical Data: A Novel Approach to Monte-Carlo-Type Conditional Stochastic Simulations and Implications for Hydrological Predictions

Geophysical techniques can help to bridge the inherent gap that exists with regard to spatial resolution and coverage for classical hydrological methods. This has led to the emergence of a new and rapidly growing research domain generally referred to as hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters, their inherent trade-off between resolution and range, as well as the notoriously site-specific nature of petrophysical parameter relations, the fundamental usefulness of multi-method surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database into a unified model of the probed subsurface region that is consistent with all available measurements. To this end, we present a novel approach toward hydrogeophysical data integration based on a Monte-Carlo-type conditional stochastic simulation method that we consider to be particularly suitable for high-resolution local-scale studies. Monte Carlo techniques are flexible and versatile, allowing for accounting for a wide variety of data and constraints of differing resolution and hardness, and thus have the potential of providing, in a geostatistical sense, realistic models of the pertinent target parameter distributions. Compared to more conventional approaches, such as co-kriging or cluster analysis, our approach provides significant ad- vancements in the way that larger-scale structural information eontained in the hydrogeophysieal data can be accounted for. After outlining the methodological background of our algorithm, we present the results of its application to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the detailed local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to a field dataset collected at the Boise Hydrogeophysical Research Site. Finally, we compare the performance of our data integration approach to that of more conventional methods with regard to the prediction of flow and transport phenomena in highly heterogeneous media and discuss the implications arising.

Conditional Simulation of Flow in Heterogeneous Porous Media with the Probabilistic Collocation Method

A stochastic approach to conditional simulation of flow in randomly heterogeneous media is proposed with the combination of the Karhunen-Loeve expansion and the probabilistic collocation method(PCM).The conditional log hydraulic conductivity field is represented with the Karhunen-Loeve expansion,in terms of some deterministic functions and a set of independent Gaussian random variables.The propagation of uncertainty in the flow simulations is carried out through the PCM,which relies on the efficient polynomial chaos expansion used to represent the flow responses such as the hydraulic head.With the PCM,existing flow simulators can be employed for uncertainty quantification of flow in heterogeneous porous media when direct measurements of hydraulic conductivity are taken into consideration.With illustration of several numerical examples of groundwater flow,this study reveals that the proposed approach is able to accurately quantify uncertainty of the flow responses conditioning on hydraulic conductivity data,while the computational efforts are significantly reduced in comparison to the Monte Carlo simulations.

Development of milk powder containing Lactobacillus plantarum NCIMB 8826 immobilized with prebiotic hi-maize starch and survival under simulated gastric and intestinal conditions

The objectives of this study were to develop a probiotic milk powder containing Lactobacillus plantarum NCIMB 8826 immobilized with prebiotic Hi-maize starch and to analyze cell viability after spray drying and exposure to simulated gastric and intestinal conditions.Milk powders containing free L.plantarum and cells immobilized with Hi-maize starch were assessed.Powders were evaluated during storage at 4°C for 15 days.After spray drying,at 0 and 15 days of storage both treatments had over 8 log CFU/g of viable cells and there were higher viable counts found for immobilized cells compared to free cells after 120 min in simulated gastric fluid.At 15 days of storage,immobilized cells had higher viable counts than free cells after exposure to simulated intestinal fluid for 120 min.The combined probiotic and prebiotic milk powder had stable viable cell counts at refrigerated storage conditions and under simulated gastric and intestinal transit.

Potential of roots and shoots of Napier grass for arresting soil erosion and runoff of mollisols soils of Himalayas

In this study, a soil filled Hydraulic Tilting Flume (HTF) was used as a test plot under simulated rainfallconditions. This flume was flled with mollisols soils (sandy loam in texture) collected from tarai regionof Himalayas. The effects of root and shoot characteristics of Napier grass in terms of leaf area index (LAI),shoot length (SL), number of leaves (NL), number of tillers (NT), shoot biomass (SB), root density (RD),root length (RL), root biomass (RB), and total biomass (TB) were investigated on runoff and sedimentoutflow at 90, 120 and 150 days after planting (DAP). Four simulated rainfall intensities namely 4.0, 6.5,8.3 and 9.4 cm/h over three land slopes of 1, 2 and 3% were selected. Runoff samples collected fromwhole plant plot and only root plot were analyzed for runoff and sediment outflow. Findings revealedthat Napier grasses were very effective to reduce runoff and sediment outflow and its efficacy increasedwith the extended growth stages. The reduction in runoff and sediment outflow at 90, 120 and 150 DAPwas obtained as 56% and 85%, 68% and 90%, and 74% and 96%, respectively, as compared to bare plotconditions. It was observed that the comparative contribution of shoots in runoff rate reduction washigher than the roots. On the contrary, the root part of the plant showed more contribution in sedimentrate reduction as compared to the shoot part. Step wise regression was attempted for the selection ofeffective input parameters to establish authentic runoff and sediment outflow models. Power form ofmultiple non-linear regression (MNLR) showed very satisfactory results for predicting runoff and sedimentoutflow with coefficient of determination (R^(2)) as 97.4% and 99.0%, respectively, root mean squareerror (RMSE) as 38.8 cc/m^(2)/min and 0.126 g/m^(2)/min, respectively, and coefficient of efficiency (CE) as93.9% and 96.7%, respectively, during testing period.

A modified zone model for estimating equivalent room thermal capacity

The zone model has been widely applied in control analysis of heating, ventilation and air conditioning （HVAC） systems to achieve a high building efficiency. This paper proposed a modified zone model which is much simpler in the HVAC system simulation and has the similar accuracy to the complicated simulation model. The proposed model took into consideration the effect of envelop heat reservoir on the room indoor temperature by introducing the thermal admittance of the inner surfaces of the building enclosure. The thermal admittance for the building enclosure was developed based on the building thermal network analytical theory and transfer function method. The efficacy of the proposed model was demonstrated by comparing it with the complicated model -- heat balance method （HTB2 program）. The predicted results from the proposed model well agreed with those from the complicated simulation. The proposed model can then make the HVAC system dynamic simulation much faster and more acceptable for control design due to its simplicity and efficiency.