Search results

A reducing variation of quality characteristics is a typical example of quality improvement. In such a case, we treat the quality characteristic, as a response variable and need to find active factors affecting the response from many candidate factors since reducing the variation of the response will be achieved by reducing variation of the active factors. In this paper, we first derive a method of selecting an active factor by linear regression. It is well known that correlation between factors deteriorates the precision of estimators. We, therefore, examine robustness of the selecting method against the correlation in the data set and derive an evaluation method of the deterioration brought by the correlation. Furthermore, some examples of selecting and evaluation methods are shown to demonstrate practical usage of the methods.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

Bridge deterioration is a critical risk to public safety, which mandates regular inspection and maintenance to ensure sustainable transport services. Many models have been developed to aid in understanding deterioration patterns and in planning maintenance actions and fund allocation. This study aims at developing a deep-learning model to predict the deterioration of concrete bridge decks.

Three long short-term memory (LSTM) models are formulated to predict the condition rating of bridge decks, namely vanilla LSTM (vLSTM), stacked LSTM (sLSTM), and convolutional neural networks combined with LSTM (CNN-LSTM). The models are developed by utilising the National Bridge Inventory (NBI) datasets spanning from 2001 to 2019 to predict the deck condition ratings in 2021.

Results reveal that all three models have accuracies of 90% and above, with mean squared errors (MSE) between 0.81 and 0.103. Moreover, CNN-LSTM has the best performance, achieving an accuracy of 93%, coefficient of correlation of 0.91, R2 value of 0.83, and MSE of 0.081.

The study used the NBI bridge inventory databases to develop the bridge deterioration models. Future studies can extend the model to other bridge databases and other applications in the construction industry.

This study provides a detailed and extensive data cleansing process to address the shortcomings in the NBI database. This research presents a framework for implementing artificial intelligence-based models to enhance maintenance planning and a guideline for utilising the NBI or other bridge inventory databases to develop accurate bridge deterioration models. Future studies can extend the model to other bridge databases and other applications in the construction industry.

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

There are various Kreis tests reported in the literature with wide variations in the procedure. The purpose of this paper is to select the most suitable and reliable method for the rancidity evaluation in ghee.

Ghee samples were prepared from butter by the direct cream method. They were assessed for early-stage oxidative deterioration by four Kreis tests in an accelerated storage trial at intervals of 48 h. The amount of ghee samples, amount of reagents (chloroform, 30 percent trichloroacetic acid, 1 percent phloroglucinol, and ethanol), incubation temperature and duration were different in the four tests. For each method, the ghee samples were also monitored for changes in flavor at intervals of 48 h by sensory evaluation. Relationships among the Kreis values determined by the four different Kreis tests and flavor scores were established using a correlation analysis.

The correlation coefficient of the Kreis values determined by different Kreis tests was in decreasing order of: Kreis test-2 (−0.904) > Kreis test-4 (−0.792) > Kreis test-3 (−0.648) > Kreis test-1 (−0.469). Thus, among the four different Kreis tests, Kreis Test-2 reported by Pool and Prater (1945) was found to be more sensitive and more consistent, and have the highest coefficient of correlation (−0.904) with flavor score of ghee during storage at 80±2°C.

The finding of this study will be useful for the selection of an appropriate and reliable Kreis test that can be used for detecting rancidity in ghee at an incipient stage. The development of rancidity in the ghee leads to formation of off-flavor and such an oxidized product is not accepted by the consumer; this leads to economic loss to the manufacturer. Detection of traces of rancidity at an early stage provides an opportunity for industry personnel to take suitable control measures and/or make decisions regarding utilization of the product.

The use of a reliable Kreis test that detects traces of rancidity in a ghee can be very useful for enabling suitable measures to be taken to prevent further oxidative deterioration or to dispose of the ghee as early as possible.

The purpose of this paper is to study the role of public and private imbalances in the cyclicality of the current account balance in a sample of advanced and developing countries. Within developing countries, the evidence does not establish the dependency of private investment on private savings and private consumption is the main driver of the saving/investment balance. In contrast, private savings seem to be better mobilized to finance private investment and the latter is the main driver of the saving/investment balance in advanced countries. Deterioration in the current account balance in response to higher private consumption could be detrimental to growth and external stability. In contrast, an investment strategy that promotes growth is likely to attract financial flows and reduce the risk of a widening current account deficit on external stability.

The paper studies determinants of the current account deficit. It studies current account fluctuations in the short‐run and explains these fluctuations by analyzing movements in the underlying components: public and private savings as well as investments and resulting imbalances. Of particular interest is the interaction between the government budget deficit, the private saving/investment balance, and the current account balance.

Using time‐series estimates, co‐movements indicate that fluctuations in the current account balance in many advanced countries appear to be driven by private investment that determines cyclicality in imports. In contrast, cyclicality in the current account appears to be driven by private consumption that determines fluctuations in imports in many developing countries. In general, fluctuations in the government budget deficit are mostly driven by government investment and fluctuations in the private saving/investment balance are mostly driven by fluctuations in private investment. Further, fluctuations in the current account balance appear to be mostly driven by fluctuations in the private saving/investment balance.

The paper explains the dynamics of the current account in relation to developments in public and private imbalances and its underlying components. It shows the effects of changes in the budget deficit and its underlying components on cyclicality in the current account. Similarly, cyclicality in the current account balance with cyclical movements in private savings and investment is studied, along with which factors affect the components of the current account balance. In particular, the paper establishes which components of the current account significantly respond to the cyclical changes in macroeconomic variables.

Automated condition surveys have been recently introduced for condition assessment of highway infrastructures worldwide. Accurate predictions of the current state, median life (ML) and future state of highway infrastructures are crucial for developing appropriate inspection and maintenance strategies for newly created as well as existing aging highway infrastructures. The paper aims to discuss these issues.

This paper proposes Markov Chain based deterioration modelling using a linear transition probability (LTP) matrix method and a median life expectancy (MLE) algorithm. The proposed method is applied and evaluated using condition improvement between the two successive inspections from the Surface Condition Assessment of National Network of Roads survey of the UK Pavement Management System.

The proposed LTP matrix model utilises better insight than the generic or decoupling linear approach used in estimating transition probabilities formulated in the past. The simulated LTP predicted conditions are portrayed in a deterioration profile and a pairwise correlation. The MLs are computed statistically with a cumulative distribution function plot.

The paper concludes that MLE is ideal for projecting half asset life, and the LTP matrix approach presents a feasible approach for new maintenance regime when more certain deterioration data become available.

The multi-scale numerical simulation method, able to represent the complexity of the random structures and capture phase degradation, is an effective way to investigate the long-term behavior of concrete in service and bridges the gap between research on the material and on the structural level. However, the combined chemical-physical deterioration mechanisms of concrete remain a challenging task. The purpose of this paper is to investigate the degradation mechanism of concrete at the waterline in cold regions induced by combined calcium leaching and frost damage.

With the help of the NIST’s three-dimensional (3D) hydration model and the random aggregate model, realistic 3D representative volume elements (RVEs) of concrete at the micro-, the meso-, and the macro-scales can be reconstructed. The boundary problem method is introduced to compute the homogenized mechanical properties for both sound and damaged RVEs. According to the damage characteristics, the staggering method including a random dissolution model and a thermo-mechanical coupling model is developed to simulate the synergy deterioration effects of interacted calcium leaching and frost attacks. The coupled damage procedure for the frost damage process is based on the hydraulic pressure theory and the ice lens growth theory considering the relationship between the frozen temperature and the radius of the capillary pore. Finally, regarding calcium leaching as the leading role in actual engineering, the numerical methodology for combined leaching and frost damage on concrete property is proposed using a successive multi-scale method.

On the basis of available experimental data, this methodology is employed to explore the deterioration process. The results agree with the experimental ones to some extent, chemical leaching leads to the nucleation of some micro-cracks (i.e. damage), and consequently, to the decrease of the frost resistance.

It is demonstrated that the multi-scale numerical methodology can capture potential aging and deterioration evolution processes, and can give an insight into the macroscopic property degradation of concrete under long-term aggressive conditions.

The study investigates the extent to which defects in coastline buildings are influenced by the climatic conditions within the coastal zones.

The study conducted both desk study and field survey. The primary data for the study were collected through a cross-sectional survey of facilities and maintenance managers of randomly selected coastline buildings. Of the 120 self-administered structured questionnaires, 102 were successfully retrieved representing an 85% response rate. Data collected were analysed using charts, relative prevalence index and Spearman's rho correlation visualization technique.

Saltwater intrusion, ocean overflow, extreme rainfall, debris flow, floods and droughts are the prevalent climatic conditions along the coastline. Steel corrosion, foundation settlement, spalling of concrete and fading of finishes are prevalent defects in coastline buildings. The result shows a positive significant correlation between climatic conditions and defects in coastline buildings.

The study compliments literature on buildings resilience and maintenance management, and also provides a basis for streamlining future research on coastline buildings.

The results provide information on climatic conditions and prevalent defects that should be considered during the design and construction of coastline buildings. The information provided could assist construction stakeholders in improving the resilience of coastline buildings.

The study established that coastline buildings are vulnerable to a rapid rate of defect and deterioration which threatens the sustainability of coastline cities. It suggests measures that could improve the resilience of the elements and components of coastline buildings and consequently enhance the safety of life and property, and improve the physical and economic performance of coastline buildings.

The purpose of this study is to find the thermo-hydraulic performances of compact heat exchangers (CHE’s), which are strongly depending upon the prediction of performance of various types of heat transfer surfaces such as offset strip fins, wavy fins, rectangular fins, triangular fins, triangular and rectangular perforated fins in terms of Colburn “j” and Fanning friction “f” factors.

Numerical methods play a major role for analysis of compact plate-fin heat exchangers, which are cost-effective and fast. This paper presents the on-going research and work carried out earlier for single-phase steady-state heat transfer and pressure drop analysis on CHE passages and fins. An analysis of a cross-flow plate-fin compact heat exchanger, accounting for the individual effects of two-dimensional longitudinal heat conduction through the exchanger wall, inlet fluid flow maldistribution and inlet temperature non-uniformity are carried out using a Finite Element Method (FEM).

The performance deterioration of high-efficiency cross-flow plate-fin compact heat exchangers have been reviewed with the combined effects of wall longitudinal heat conduction and inlet fluid flow/temperature non-uniformity using a dedicated FEM analysis. It is found that the performance deterioration is quite significant in some typical applications due to the effects of wall longitudinal heat conduction and inlet fluid flow non-uniformity on cross-flow plate-fin heat exchangers. A Computational Fluid Dynamics (CFD) program FLUENT has been used to predict the design data in terms of “j” and “f” factors for plate-fin heat exchanger fins. The suitable design data are generated using CFD analysis covering the laminar, transition and turbulent flow regimes for various types of fins.

The correlations for the friction factor “f” and Colburn factor “j” have been found to be good. The correlations can be used by the heat exchanger designers and can reduce the number of tests and modification of the prototype to a minimum for similar applications and types of fins.