Concrete Overstrength: Assessment of Field Strength Seeking Insights for Overdesign Optimization

This study investigates the high contents of cementitious materials in Portland cement concrete and assesses the required (f’cr) and actual (σ) compressive strength of concrete specimens. A linear optimization technique identifies the required binder content to reach f’cr. Standard specifications have required concrete overdesign (OD) for decades, but few studies have evaluated the actual magnitude of OD from field data. The compressive strength of 958 cylinders prepared in the field represented 8200 m3 of ready-mixed concrete with 300 and 450 kg/m3 of cementitious are analyzed. The actual OD appears to be 7 to 21% higher than required. The required 28-day compressive strength of concrete was achieved in less than seven days. Therefore, the content of the cementitious materials could be reduced by 6 and 17% so that concrete could reach f’cr without cementitious overconsumption. Reducing cementitious content is recommended to improve construction quality and optimize resource utilization. Among the main reasons for this recommendation are the estimated substantial long-term savings, increased concrete durability and more rational use of natural resources required to build the structures.

Experimental Study on the Reliability of Scaling Down Techniques Used in Direct Shear Tests to Determine the Shear Strength of Rockfill and Waste Rocks

The determination of shear strength parameters for coarse granular materials such as rockfill and waste rocks is challenging due to their oversized particles and the minimum required ratio of 10 between the specimen width (W) and the maximum particle size (dmax) of tested samples for direct shear tests. To overcome this problem, a common practice is to prepare test samples by excluding the oversized particles. This method is called the scalping scaling down technique. Making further modifications on scalped samples to achieve a specific particle size distribution curve (PSDC) leads to other scaling down techniques. Until now, the parallel scaling down technique has been the most popular and most commonly applied, generally because it produces a PSDC parallel and similar to that of field material. Recently, a critical literature review performed by the authors revealed that the methodology used by previous researchers to validate or invalidate the scaling down techniques in estimating the shear strength of field materials is inappropriate. The validity of scaling down techniques remains unknown. In addition, the minimum required W/dmax ratio of 10, stipulated in ASTM D3080/D3080M-11 for direct shear tests, is not large enough to eliminate the specimen size effect (SSE). The authors’ recent experimental study showed that a minimum W/dmax ratio of 60 is necessary to avoid any SSE in direct shear tests. In this study, a series of direct shear tests were performed on samples with different dmax values, prepared by applying scalping and parallel scaling down techniques. All tested specimens had a W/dmax ratio equal to or larger than 60. The test results of the scaled down samples with dmax values smaller than those of field samples were used to establish a predictive equation between the effective internal friction angle (hereafter named “friction angle”) and dmax, which was then used to predict the friction angles of the field samples. Comparisons between the measured and predicted friction angles of field samples demonstrated that the equations based on scalping scaling down technique correctly predicted the friction angles of field samples, whereas the equations based on parallel scaling down technique failed to correctly predict the friction angles of field samples. The scalping down technique has been validated, whereas the parallel scaling down technique has been invalidated by the experimental results presented in this study.

Effect of Aramid Fibers on Balanced Mix Design of Asphalt Concrete

Fiber-reinforced asphalt concrete (FRAC) was tested using limestone, PG 64-22 binder, and 20% reclaimed asphalt pavement (RAP). After mixing fibers with different lengths and dosages, they were extracted and recovered to evaluate their dispersion in the FRAC. The uniaxial fatigue test, IDEAL CT test, and flow number test were performed on FRAC with different fiber lengths and asphalt contents. The balanced mix design (BMD) approach was then used to analyze the uniaxial and flow number test results in order to evaluate the effect of aramid fibers on fatigue and rutting resistance of the pavement. The dispersion test showed that the 19 mm and 10 mm aramid fibers at a dosage rate of 0.5 g/kg provided the best dispersion. The 19 mm fibers showed better performance test results than the 10 mm and 38 mm fibers. The BMD approach provided ranges of asphalt contents to produce mixes with certain resistances to fatigue and rutting. The BMD approach also demonstrated the effect of fibers with different lengths on increasing the resistance to fatigue and rutting. The study concluded that the 19 mm fibers with a dosage of 0.5 g/kg produce best results. The BMD approach is a good tool that can be used to refine the mix ingredients, including additives such as fibers, in order to optimize pavement resistance to various distresses such as fatigue cracking and rutting.

An Analysis of Local and Combined (Global) Scours on Piers-on-Bank Bridges

This paper examines the scour problems related to piers-on-bank bridges resulting from frequently flooded and/or constricted waterways. While local scour problems for bridge piers in riverine channels have been addressed extensively in the literature, there have been few studies addressing piers-on-bank scour scenarios. A comprehensive three-dimensional finite element analysis using the element removal (ER) technique has been performed on a recently constructed bridge with an observable scour problem on multiple piers. The analysis is further extended to study the effect of “combined scour” or extensive erosion of soil between adjacent piles. Three different loading cases were considered in the study, and the results demonstrated that the effects of local and combined scours on bridge drilled shaft foundations can be significant under the combined actions of axial, lateral loads and bending moments. Specifically, the most critical case of combined scour is when maximum moment effect is applied to the piers. The results of this study show that the interaction of soil displacement fields between adjacent piles should be investigated for bridge crossings with piers-on-bank, with a high risk of flooding during the moderate-to-low probability of the occurrence of precipitation events, as they can increase the pile head displacements and the bending moments in the soil and result in the early failure of bridges.

Assessing the Capability of Computational Fluid Dynamics Models in Replicating Wind Tunnel Test Results for the Rose Fitzgerald Kennedy Bridge

Despite its wide acceptance in various industries, CFD is considered a secondary option to wind tunnel tests in bridge engineering due to a lack of confidence. To increase confidence and to advance the quality of simulations in bridge aerodynamic studies, this study performed three-dimensional RANS simulations and DESs to assess the bridge deck aerodynamics of the Rose Fitzgerald Kennedy Bridge and demonstrated detailed procedures of the verification and validation of the applied CFD model. The CFD simulations were developed in OpenFOAM, the results of which are compared to prior wind tunnel test results, where general agreements were achieved though differences were also found and analyzed. The CFD model was also applied to study the effect of fascia beams and handrails on the bridge deck aerodynamics, which were neglected in most research to-date. These secondary structures were found to increase drag coefficients and reduce lift and moment coefficients by up to 32%, 94.3%, and 52.2%, respectively, which emphasized the necessity of including these structures in evaluations of the aerodynamic performance of bridges in service. Details of the verification and validation in this study illustrate that CFD simulations can determine close results compared to wind tunnel tests.

Automatic Assessment of Buildings Location Fitness for Solar Panels Installation Using Drones and Neural Network

Solar panel location assessment is usually a time-consuming manual process, and many criteria should be taken into consideration before deciding. One of the most significant criteria is the building location and surrounding environment. This research project aims to propose a model to automatically identify potential roof spaces for solar panels using drones and convolutional neural networks (CNN). Convolutional neural networks (CNNs) are used to identify buildings’ roofs from drone imagery. Transfer learning on the CNN is used to classify roofs of buildings into two categories of shaded and unshaded. The CNN is trained and tested on separate imagery databases to improve classification accuracy. Results of the current project demonstrate successful segmentation of buildings and identification of shaded roofs. The model presented in this paper can be used to prioritize the buildings based on the likelihood of getting benefits from switching to solar energy. To illustrate an implementation of the presented model, it has been applied to a selected neighborhood in the city of Hurricane in West Virginia. The research results show that the proposed model can assist investors in the energy and building sectors to make better and more informed decisions.

Controlling Switchable Electrochromic Glazing for Energy Savings, Visual Comfort and Thermal Comfort: A Model Predictive Control

Dynamic façades play an important role in enhancing the overall performance of buildings: they respond to the environmental conditions and adjust the amount of transmitted solar radiation. This paper proposes a simulation-based framework to evaluate the energy and comfort performance of different control strategies for switchable electrochromic glazing (EC). The presented method shows the impact of a model predictive control (MPC) on energy savings and on visual and thermal comfort for different orientations compared to other strategies. Besides manual operation and conventional rule-based controls, the benchmark in this study was a simulation-based control (multi-objective penalty-based control) with optimal performance. The hourly results of various control cases were analyzed based on the established performance indicators and criteria. The cumulative annual results show the capabilities and limitations of each control strategy for an EC glazing. For a temperate climate (Mannheim, Germany), results showed that an MPC for EC glazing provides visual and thermal comfort while saving energy of up to 14%, 37%, 37%, and 34% respectively for facing north, east, south, and west relative to the base-case.

A Comparative Study on the Effect of Class C and Class F Fly Ashes on Geotechnical Properties of High-Plasticity Clay

Clays generally have a low strength and capacity, and additives are usually used to stabilize them. In recent years, using fly ash to stabilize soil has decreased environmental pollution while also having an economic benefit. The objective of this study is to perform a comparative investigation on the effect of class C and class F fly ashes on geotechnical properties of high-plasticity clay using the Atterberg’s limit, compaction, California Bearing Ratio (CBR), and unconfined compressive strength tests. The results showed that with an increase in the amount of fly ash, there was a decrease in the maximum dry density and an increase in the optimum moisture content. Moreover, an addition of fly ashes of up to 25% caused a reduction of the liquid limit and plasticity index, and an increase in the maximum unconfined compressive strength and CBR. Lengthening the curing time had a positive impact on the unconfined compressive strength of the soil. The soil samples with class C fly ash were seen to possess more efficient geotechnical properties as compared to class F fly ash.

Knowledge Discovery by Analyzing the State of the Art of Data-Driven Fault Detection and Diagnostics of Building HVAC

The automated fault detection and diagnostics (AFDD) of heating, ventilation, and air conditioning (HVAC) using data mining and machine learning models have recently received substantial attention from researchers and practitioners. Various models have been developed over the years for AFDD of complete HVAC or its sub-systems. However, HVAC complexities, which partly have roots in its close coupling nature and interrelated dependencies, mean that understanding the relationship between faults and the suitability of the techniques remains an unanswered question. The literature analysis and interactive visualization of the data collected from the past implementation of AFDD models can provide useful insight to further explore this question by applying artificial intelligence (AI). Association rule mining (ARM) is deployed by this paper, using the frequent pattern (FP) growth algorithm to generate frequent fault sets for most common HVAC faults from the body of AFDD models developed in the literature to represent the status quo. A new model is developed for common HVAC faults and the techniques most frequently used to detect and diagnose them. A recommender system is developed using the ARM model to extract knowledge from the body of knowledge of HVAC data-driven AFDD in the form of rule-sets that reflect the associations. Findings of this review paper can significantly help civil and building engineers, as well as facility managers, in better management of building HVAC systems.

Numerical Analysis of an Earthen Masonry Structure Subjected to Blast Loading

Historic monuments and construction capture the knowledge of civilizations of the past and are a source of pride for people of the present. Over the centuries, these buildings have been at risk from natural and man-made causes. The Alhambra, a UNESCO World Heritage Site in Granada, Spain, is one of such places. This paper aims to evaluate the structural performance of the Torre de la Vela, a tower in the Alhambra, under blast loads. The loads were based on historical records of barrels of gunpowder and were modeled as simplified pressure profiles using existing empirical equations. The effect of impulsive loading on the material properties was accounted for using dynamic increase factors, determined experimentally by previous authors. The model was created using finite element methods (FEM) and the problem was solved using explicit dynamic analysis available in Abaqus/Explicit. Using the failure volume damage index, a blast load applied outside and inside of the building would create a low damage level, which should be treated with caution given the occurrence of localized damage. The removal of elements exceeding a given damage threshold led to more visible damage patterns than the Concrete Tension Damage option in Abaqus.