Minimum Design Loads for Buildings and Other Structures provides requirements for general structural design and includes means for determining dead, live, soil, flood, wind, snow, rain, atmospheric ice, and earthquake loads, as well as their combinations, which are suitable for inclusion in building codes and other documents. This Standard, a revision of ASCE/SEI 7-05, offers a complete update and reorganization of the wind load provisions, expanding them from one chapter into six. The Standard contains new ultimate event wind maps with corresponding reductions in load factors, so that the loads are not affected, and updates the seismic loads with new risk-targeted seismic maps. The snow, live, and atmospheric icing provisions are updated as well. In addition, the Standard includes a detailed Commentary with explanatory and supplementary information designed to assist building code committees and regulatory authorities. Standard ASCE/SEI 7 is an integral part of building codes in the United States. Many of the load provisions are substantially adopted by reference in the International Building Code and the NFPA 5000 Building Construction and Safety Code. Structural engineers, architects, and those engaged in preparing and administering local building codes will find this Standard an essential reference in their practice. Note: New orders are fulfilled from the second printing, which incorporates the errata to the first printing.

Minimum Design Loads for Buildings and Other Structures

Wind speeds over the world’s oceans have increased over the past two decades, as have wave heights. Studies of climate change typically consider measurements or predictions of temperature over extended periods of time. Climate, however, is much more than temperature. Over the oceans, changes in wind speed and the surface gravity waves generated by such winds play an important role. We used a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. We find a general global trend of increasing values of wind speed and, to a lesser degree, wave height, over this period. The rate of increase is greater for extreme events as compared to the mean condition.

https://researchbank.swinburne.edu.au/file/bca43746-6f16-4ad2-a4b7-27f8d8d60fed/1/PDF (Published version).pdf

Global trends in wind speed and wave height over the past 25 years

Metallic biomaterials are used in medical devices in humans more than any other family of materials. The corrosion resistance of an implant material affects its functionality and durability and is a prime factor governing biocompatibility. The fundamental paradigm of metallic biomaterials, except biodegradable metals, has been “the more corrosion resistant, the more biocompatible.” The body environment is harsh and raises several challenges with respect to corrosion control. In this invited review paper, the body environment is analysed in detail and the possible effects of the corrosion of different biomaterials on biocompatibility are discussed. Then, the kinetics of corrosion, passivity, its breakdown and regeneration in vivo are conferred. Next, the mostly used metallic biomaterials and their corrosion performance are reviewed. These biomaterials include stainless steels, cobalt-chromium alloys, titanium and its alloys, Nitinol shape memory alloy, dental amalgams, gold, metallic glasses and biodegradable metals. Then, the principles of implant failure, retrieval and failure analysis are highlighted, followed by description of the most common corrosion processes in vivo. Finally, approaches to control the corrosion of metallic biomaterials are highlighted.

Corrosion of Metallic Biomaterials: A Review

Piezoelectric coefficients are constrained by the intrinsic crystal structure of the constituent material. Here we describe design and manufacturing routes to previously inaccessible classes of piezoelectric materials that have arbitrary piezoelectric coefficient tensors. Our scheme is based on the manipulation of electric displacement maps from families of structural cell patterns. We implement our designs by additively manufacturing free-form, perovskite-based piezoelectric nanocomposites with complex three-dimensional architectures. The resulting voltage response of the activated piezoelectric metamaterials at a given mode can be selectively suppressed, reversed or enhanced with applied stress. Additionally, these electromechanical metamaterials achieve high specific piezoelectric constants and tailorable flexibility using only a fraction of their parent materials. This strategy may be applied to create the next generation of intelligent infrastructure, able to perform a variety of structural and functional tasks, including simultaneous impact absorption and monitoring, three-dimensional pressure mapping and directionality detection. Piezoelectrics convert force into electrical charge, and vice versa, but the coefficients that determine piezoelectric behaviour are constrained by crystal structure. Here, metamaterials are 3D printed that show arbitrary piezoelectric coefficients.

Three-dimensional printing of piezoelectric materials with designed anisotropy and directional response.

Cyclic performance of extended end-plate connections equipped with shape memory alloy bolts

Yonjung Bridge is a hybrid multispan bridge that is designed to transport high-speed trains (HEMU-430X) with maximum operating speed of 430 km/h. The bridge consists of simply supported prestressed concrete (PSC) and composite steel girders to carry double railway tracks. The structural health monitoring system (SHM) is designed and installed to investigate and assess the performance of the bridge in terms of acceleration and deformation measurements under different speeds of the passing train. The SHM measurements are investigated in both time and frequency domains; in addition, several identification models are examined to assess the performance of the bridge. The drawn conclusions show that the maximum deflection and acceleration of the bridge are within the design limits that are specified by the Korean and European codes. The parameters evaluation of the model identification depicts the quasistatic and dynamic deformations of PSC and steel girders to be different and less correlated when higher speeds of the passing trains are considered. Finally, the variation of the frequency content of the dynamic deformations of the girders is negligible when high speeds are considered.

/pdf/yonjung-high-speed-railway-bridge-assessment-using-output-3ieyc9107f.pdf

Yonjung High-Speed Railway Bridge Assessment Using Output-Only Structural Health Monitoring Measurements under Train Speed Changing

The geodetic datum transformation in-between local and global systems seen in the world are inspiring for the engineering applications. In this context, the Egyptian geodetic network has a limited observation for the terrestrial and satellite of the geodetic networks. Transforming the coordinates of the Egyptian datum, here we demonstrate the datum transformation in three directions from global to local coordinates that utilized the artificial neural network (ANN) technique as a new tool of datum transformation in Egypt. A conventional, which are the Helmert and Molodensky, and numerical, which are the regression, minimum curvature surface, and ANN, datum transformation techniques are investigated and compared over the available data in Egypt. The results showed an accurate transforming datum using ANN technique for both common and check points, and the novel model improved the transformation coordinates by 37 to 72% in space directions. A comparison between the conventional and numerical techniques shows that the accuracy of the developed ANN model is 20.16 cm in terms of standard deviation based on the residuals of the projected coordinates.

A novel three-direction datum transformation of geodetic coordinates for Egypt using artificial neural network approach

The characteristics of fresh and hardened self-compacting concrete (SCC) are an essential requirement for construction projects. Moreover, the sensitivity of admixture contents of SCC in these properties is highly impacted by that cost. The current study investigates to estimate the slump-flow (S) and compressive strength (CS), as fresh and hardened properties of SCC, respectively. Four developed soft-computing approaches were proposed and compared, including the group method of data handling (GMDH), Minimax Probability Machine Regression (MPMR), emotional neural network (ENN), and hybrid artificial neural network-particle swarm optimization (ANN-PSO), to estimate the S and 28-day CS of SCC, which comprises fly ash (FA), silica fume (SF), and limestone powder (LP) as part of cement by mass in total powder content. In addition, the impact of eight admixture components is investigated and evaluated to assess the sensitivity of admixture contents for the modelling of S and CS of SCC. The results demonstrate that the performance prediction of ENN model is more significant than other models in estimating S and CS characteristics of SCC. The overall of Pearson correlation coefficient, r, and root mean square error (RMSE) of ENN model are 97.80% and 20.16 mm, respectively, for the S. These are 96.07% and 2.59 MPa, respectively, for the CS. Furthermore, the sensitivity of the powder content of fly ash is shown to have a high impact on the estimated S and CS values of SCC.

Estimating Slump Flow and Compressive Strength of Self-Compacting Concrete Using Emotional Neural Networks

This paper explores strength, stiffness and rotational capacity rotational in thick top-and-seat (cleated) angle connections subjected to monotonic and cyclic loads. The results of test on two full-scale connections are described first, and are then compared to published curve-fitting models for these types of connections. The data indicate that the curve-fitting constants of some existing mathematical models cannot be extrapolated to thick angles. The experimental results also show that these connections are capable of providing very ductile behavior and constitute an ideal back-up structural system in steel frames.

Rotational capacity and demand in top-and-seat angle connections subjected to seismic loading

Steel plate shear walls are recently used as efficient seismic lateral resisting systems. These lateral resistant structures are implemented to provide more strength, stiffness and ductility in limited space areas. In this study, the seismic behavior of the multi-story steel frames with steel plate shear walls are investigated for buildings with 4, 8, 12 and 16 stories using verified computational modeling platforms. Different number of steel moment bays with distinctive lengths are investigated to effectively determine the deflection amplification factor for low-rise and high-rise structures. Results showed that the dissipated energy in moment frames with steel plates are significantly related to the inside panel. It is shown that more than 50% of the dissipated energy under various ground motions is dissipated by the panel itself, and increasing the steel plate length leads to higher energy dissipation capability. The deflection amplification factor is studied in details for various verified parametric cases, and it is concluded that for a typical multi-story moment frame with steel plate shear walls, the amplification factor is 4.93 which is less than the recommended conservative values in the design codes. It is shown that the deflection amplification factor decreases if the height of the building increases, for which the frames with more than six stories would have less recommended deflection amplification factor. In addition, increasing the number of bays or decreasing the steel plate shear wall length leads to a reduction of the deflection amplification factor.

Jong Wan Hu

Papers

Yonjung High-Speed Railway Bridge Assessment Using Output-Only Structural Health Monitoring Measurements under Train Speed Changing

A novel three-direction datum transformation of geodetic coordinates for Egypt using artificial neural network approach

Estimating Slump Flow and Compressive Strength of Self-Compacting Concrete Using Emotional Neural Networks

Rotational capacity and demand in top-and-seat angle connections subjected to seismic loading

Seismic behavior investigation of the steel multi-story moment frames with steel plate shear walls