This article aims to review and analyze the aspects and characteristics related to infrared food drying. Indeed, with a review of 100 relevant publications all dealing with infrared food drying, this article notes that infrared drying has several advantages over other common food drying methods. Shorter drying time, a better final dried product quality, and more energy savings in the process are revealed as the most important advantages of infrared drying over convective heat drying. Infrared dryers can also be easily combined with other drying methods such as hot air, microwave, vibration, and vacuum. This article clearly shows that using infrared heating for food drying purposes has become more popular in the last decade and its application in the industrial drying of different foodstuffs has been employed widely.

Infrared Heating in Food Drying: An Overview

The findings of a current research project entitled Thermal Effects in Concrete Bridge Superstructures are highlighted. The research project is sponsored by NCHRP. A brief discussion of the mechanisms of heat transfer as they relate to bridge structures is presented, including the thermal coefficients of various types of different concrete composed of different aggregates. Also included are brief discussions on mean effective bridge temperatures, temperature differentials, and the response analysis for nonlinear temperature gradients. Two case studies of longitudinal thermal response selected from those conducted in the research from those conducted in the research project are included in this paper. The thermal gradients used in New Zealand, England, and Ontario, Canada, plus those recommended by the Post-Tensioning Institute, are included in the reesponse analysis. In addition, specific recommendations for improving the U.S. design provisions for thermal effects are included. (Author)

Thermal effects in concrete bridge superstructures

Calcium carbide, a stable solid compound composed of two atoms of carbon and one of calcium, has proven its effectiveness in chemical synthesis, due to the safety and convenience of handling the C≡C acetylenic units. The areas of CaC2 application are very diverse, and the development of calcium-mediated approaches resolves several important challenges. This Review aims to discuss the laboratory chemistry of calcium carbide, and to go beyond its frontiers to organic synthesis, life sciences, materials and construction, carbon dioxide capturing, alloy manufacturing, and agriculture. The recyclability of calcium carbide and the availability of large-scale industrial production facilities, as well as the future possibility of fossil-resource-independent manufacturing, position this compound as a key chemical platform for sustainable development. Easy regeneration and reuse of the carbide highlight calcium-based sustainable chemical technologies as promising instruments for total carbon recycling.

Calcium-Based Sustainable Chemical Technologies for Total Carbon Recycling

Grand global challenges of our time, such as food security and soil security, cannot be met without up-to-date, high-quality, high-resolution, spatiotemporal, and continuous soil and environmental data that characterize soil ecosystems. At local and regional scales, accurate and precise soil assessment is critical for management, soil health, and sustainability. This article presents integration pathways fusing lab- and field-based soil measurements, proximal and remote sensor data, environmental covariates, and/or methods within the framework of the Meta Soil Model which is poised to extend contemporary soil applications. The STEP-AWBH model allows to quantify soil-environmental covariates ( S : soil, T : topography, E : ecology, P : parent material, A : atmosphere, W : water, B : biota, H : human factors) of which numerous can be sensed. We present an in-depth overview of proximal and remote sensor technologies that are used in the realm of digital soil assessment. Specific attention is given to the fusion process of (1) proximal, (2) proximal/remote, and (3) remote sensors to directly sense or predict soil properties. We highlight the promises and perils of sensor-derived proxies that allow inferences on soil properties and their change. From our review it is evident that there is no such single sensor or method that fits all soil applications. In many studies the fusion/integration of data and methods enhance the capabilities to assess specific soil properties. We critically contrast the benefits and constraints of proximal and remote sensing, fusion of soil-environmental data, and integration pathways to mash data and methods into complex soil assessments.

Fusion of Soil and Remote Sensing Data to Model Soil Properties

Compression index Cc is an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge. This paper suggests a novel modelling approach using machine learning (ML) technique. The performance of five commonly used machine learning (ML) algorithms, i.e. back-propagation neural network (BPNN), extreme learning machine (ELM), support vector machine (SVM), random forest (RF) and evolutionary polynomial regression (EPR) in predicting Cc is comprehensively investigated. A database with a total number of 311 datasets including three input variables, i.e. initial void ratio e0, liquid limit water content wL, plasticity index Ip, and one output variable Cc is first established. Genetic algorithm (GA) is used to optimize the hyper-parameters in five ML algorithms, and the average prediction error for the 10-fold cross-validation (CV) sets is set as the fitness function in the GA for enhancing the robustness of ML models. The results indicate that ML models outperform empirical prediction formulations with lower prediction error. RF yields the lowest error followed by BPNN, ELM, EPR and SVM. If the ranges of input variables in the database are large enough, BPNN and RF models are recommended to predict Cc. Furthermore, if the distribution of input variables is continuous, RF model is the best one. Otherwise, EPR model is recommended if the ranges of input variables are small. The predicted correlations between input and output variables using five ML models show great agreement with the physical explanation.

Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms

This report presents findings of a literature review, a field trip, and a finite element analysis pertaining to integral bridges. The purpose of the report is to identify problems and uncertainties, and to gain insight into the interactions between the foundation piles, the integral abutment, and the surrounding ground. The field trip included visits to six bridges arranged by Mr. Park Thompson from the Staunton district. Pertinent literature is reviewed and findings are presented. Important factors identified on the basis of this review are settlement of the approach fill, loads on the abutment piles, the nature of the abutment displacements and the associated earth pressure distribution, secondary loads on the superstructure, and soil structure interaction effects. The causes of approach fill settlement and possible mitigation techniques are discussed. Recommendations for improving the performance of integral bridges are included, and actions for improvement of integral bridge behavior are suggested.

The behavior of integral abutment bridges

This paper presents results from an experimental study of semiintegral bridge abutments. Primary aims were to investigate: 1) potential problems with the particular detail tested; 2) rotational characteristics of the semiintegral abutments; and 3) ability of specimens to withstand cyclic loading induced by temperature variations during the expected life of the bridge. 16 experiments were conducted on 3 large-scale specimens. Test results have shown that semiintegral abutments can significantly reduce the moments transferred from the superstructure to the foundation piles. Test results have also shown that semiintegral abutments can tolerate the number of displacement cycles that a bridge will experience during the course of its economic life.

Behavior of a Semiintegral Bridge Abutment under Static and Temperature-Induced Cyclic Loading

Cyclic lateral load tests simulating 75 years of bridge life were performed on an H-pile, a pipe pile, and a prestressed reinforced concrete pile by applying over 27,000 displacement cycles The data from the tests indicate that steel H-piles loaded on the weak axis are the best pile type for support of integral abutment bridges Concrete piles are not recommended for integral bridge support because, under repeated lateral loads, tension cracks progressively worsen and significantly reduce vertical load carrying capacity of these piles Steel pipe piles are stiffer than H-piles loaded on the weak axis, and therefore induce higher stresses in the abutment where they are embedded

Performance of piles supporting integral bridges

Enhancing TDR based water content measurements by ANN in sandy soils

As the temperature of an integral bridge changes, the length of the bridge increases and decreases, so that the abutments are pushed against the approach fill and then pulled away, causing lateral deflections at the tops of the piles that support the bridge. As a result, complex interactions take place among the abutment, the approach fill, the foundation soil, and the piles supporting integral bridges. Finite element analyses were performed to investigate these complex interactions. The results of this study indicate that these interactions have a beneficial effect on the stresses in the piles supporting the bridges. Because of these interactions, the foundation soil acts as if it were softer, resulting in reduced shear and moment in the piles at a given amount of deflection at the tops of the piles and therefore reduced stresses in the piles.

Sami Arsoy

Papers

The behavior of integral abutment bridges

Behavior of a Semiintegral Bridge Abutment under Static and Temperature-Induced Cyclic Loading

Performance of piles supporting integral bridges

Enhancing TDR based water content measurements by ANN in sandy soils

Effect of Bridge-Soil Interaction on Behavior of Piles Supporting Integral Bridges