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The partially prestressed concrete beam with unbonded tendon is still an active field of research because of the difficulty in analyzing and understanding its behavior. The finite-element (FE) simulation of such beams using numerical software is very scarce in the literature and therefore this study is taken to demonstrate the modeling aspects of unbonded partially prestressed concrete (UPPSC) beams. This study aims to present the three-dimensional (3-D) nonlinear FE simulations of UPPSC beams subjected to monotonic static loadings using the numerical analysis package ANSYS.

The sensitivity study is carried out with three different mesh densities to obtain the optimum elements that reflect on the load–deflection behavior of numerical models, and the model with optimum element density is used further to model all the UPPSC beams in this study. Three half-symmetry FE model is constructed in ANSYS parametric design language domain with proper boundary conditions at the symmetry plane and support to achieve the same response as that of the full-scale experimental beam available in the literature. The linear and nonlinear material behavior of prestressing tendon and conventional steel reinforcements, concrete and anchorage and loading plates are modeled using link180, solid65 and solid185 elements, respectively. The Newton–Raphson iteration method is used to solve the nonlinear solution of the FE models.

The evolution of concrete cracking at critical loadings, yielding of nonprestressed steel reinforcements, stress increment in the prestressing tendon, stresses in concrete elements and the complete load–deflection behavior of the UPPSC beams are well predicted by the proposed FE model. The maximum discrepancy of ultimate moments and deflections of the validated FE models exhibit 13% and −5%, respectively, in comparison with the experimental results.

The FE analysis of UPPSC beams is done using ANSYS software, which is a versatile tool in contrast to the experimental testing to study the stress increments in the unbonded tendons and assess the complete nonlinear response of partially prestressed concrete beams. The validated numerical model and the techniques presented in this study can be readily used to explore the parametric analysis of UPPSC beams.

The developed model is capable of predicting the strength and nonlinear behavior of UPPSC beams with reasonable accuracy. The load–deflection plot captured by the FE model is corroborated with the experimental data existing in the literature and the FE results exhibit good agreement against the experimentally tested beams, which expresses the practicability of using FE analysis for the nonlinear response of UPPSC beams using ANSYS software.

The current methods for inspecting tall or deep structures such as towers, chimneys, silos, and wells suffer from certain constraints. Manual and assisted inspection methods including humans, drones, wall climbing robots, and others are either costly, have a limited operation time, or affected by field conditions, such as temperature and radiation. This study aims to overcome the presented challenges through a teleoperated soft continuum manipulator capable of inspecting tall or deep structures with high resolution, an unlimited operation time and the ability to use different arms of the manipulator for different environments and structure sizes.

The teleoperated manipulator uses one rotary and two tendon actuators to reach and inspect the interior of a tall (or deep) structure. A sliding part along the manipulator’s body (arm constrainer and tendon router) induces a variable-length bending segment, allowing an inspection camera to be placed at different distances from the desired location.

The experiments confirmed the manipulator’s ability to inspect different locations in the structure’s interior. The manipulator also demonstrated a submillimeter motion resolution vertically and a 2.5 mm per step horizontally. The inspection time of the full structure was 48.53 min in the step-by-step mode and was calculated to be 4.23 min in the continuous mode.

The presented manipulator offers several design novelties: the arm’s thin-wide cross-section, the variable-length bending segment in a fixed-length body, the external rolling tendon routing and the ability to easily replace the arm with another of different material or dimensions to suite different structures and environments.

Stiffness adjusting ability is essential for soft robotic arms to perform complex tasks. A soft state enables dexterous operation and safe interaction, while a rigid state enables large force output or heavy weight carrying. However, making a compact integration of soft actuators with powerful stiffness adjusting mechanisms is challenging. This study aims to develop a piston-like particle jamming mechanism for enhanced stiffness adjustment of a soft robotic arm.

The arm has two pairs of differential tendons for spatial bending, and a jamming core consists of four jamming units with particles sealed inside braided tubes for stiffness adjustment. The jamming core is pushed and pulled smoothly along the tendons by a piston, which is then driven by a motor and a ball screw mechanism.

The tip displacement of the arm under 150 N jamming force and no more than 0.3 kg load is minimal. The maximum stiffening ratio measured in the experiment under 150 N jamming force is up to 6–25 depends on the bending direction and added load of the arm, which is superior to most of the vacuum powered jamming method.

The proposed robotic arm makes an innovative compact integration of tendon-driven robotic arm and motor-driven piston-like particle jamming mechanism. The jamming force is much larger compared to conventional vacuum-powered systems and results in a superior stiffening ability.

This study aims to improve the muscle model control performance of a tendon-driven musculoskeletal system (TDMS) to overcome disadvantages such as multisegmentation and strong coupling. An adaptive network controller (ANC) with a disturbance observer is established to reduce the modeling error of the musculoskeletal model and improve its antidisturbance ability.

In contrast to other control technologies adopted for musculoskeletal humanoids, which use geometric relationships and antagonist inhibition control, this study develops a method comprising of three parts. (1) First, a simplified musculoskeletal model is constructed based on the Taylor expansion, mean value theorem and Lagrange–d’Alembert principle to complete the decoupling of the muscle model. (2) Next, for this simplified musculoskeletal model, an adaptive neuromuscular controller is designed to acquire the muscle-activation signal and realize stable tracking of the endpoint of the muscle-driven robot relative to the desired trajectory in the TDMS. For the ANC, an adaptive neural network controller with a disturbance observer is used to approximate dynamical uncertainties. (3) Using the Lyapunov method, uniform boundedness of the signals in the closed-loop system is proved. In addition, a tracking experiment is performed to validate the effectiveness of the adaptive neuromuscular controller.

The experimental results reveal that compared with other control technologies, the proposed design techniques can effectively improve control accuracy. Moreover, the proposed controller does not require extensive considerations of the geometric and antagonistic inhibition relationships, and it demonstrates anti-interference ability.

Musculoskeletal robots with humanoid structures have attracted considerable attention from numerous researchers owing to their potential to avoid danger for humans and the environment. The controller based on bio-muscle models has shown great performance in coordinating the redundant internal forces of TDMS. Therefore, adaptive controllers with disturbance observers are designed to improve the immunity of the system and thus directly regulate the internal forces between the bio-muscle models.

This study focused on identifying critical factors governing the fire response of prestressed hollow-core slabs. The hollow-core slabs used as flooring units can be subjected to elevated temperatures during a fire. The fire response of prestressed hollow-core slabs is required to develop slabs with greater fire endurance. The present study aims to determine the extent to which the hollow-core slab can sustain load during a fire without undergoing progressive collapse under extreme fire and heating scenarios.

A finite element model was generated to predict the fire response of prestressed hollow core slabs under elevated temperatures. The accuracy of the model was predicted by examining thermal and structural responses through coupled temperature displacement analysis. A sensitivity analysis was performed to study the effects of concrete properties on prediction of system response. A parametric study was conducted by varying the thickness of the slab, fire and heating scenarios.

Thermal conductivity and specific heat of concrete were determined as sensitive parameters. The thickness of the slab was identified as a critical factor at a higher load level. Asymmetric heating of the slab resulted in higher fire resistance compared with symmetric heating.

This is the first study focused on studying the effect of modeling uncertainties on the system response by sensitivity analysis under elevated temperatures. The developed model with a parametric study helps in identifying critical factors for design purposes.

This study aims to explore the potential benefits favoring the adaptation of structural optimization techniques in the additive manufacturing (AM) of medical utilities to meet the repetitive demand for functionally precise customized orthoses. Irregularities encountered during the conventional treatment of tendon injuries can be eschewed using advanced structural simulation in design and innovative splint fabrication using 3D printing.

A customized mallet finger splint designed from 3D scans was subjected to ANSYS topological simulation comprising multi-level weight reduction to retain optimal mass (100%, 90%, 80%, 70% and 60%). A batch of the four typical 3D printing materials was chosen to conduct a comparative mechanical and thermal stress analysis, facilitating the selection of the optimal one for fabricating functionally adaptive splints. Assurance of structural safety was accomplished through the experimental validation of simulation results against the testing data set of ASTM D695 and ASTM D638 Type-1 specimens over a universal testing machine (UTM). Fused deposition modeling (FDM) 3D printing processed the optimized splint fabrication to assist evaluation of weight reduction percentage, fitting aesthetics, appearance, comfort, practicality and ventilation ease at the user end.

AM efficacy can efficiently execute the design complexity involved in the topology optimization (TO) results and introduces rehabilitation practicality into the application. Topologically optimized splint provided with favorable comfort, stiffness and strengthening features, offers ventilation ease and structural stability for customized appliances, with 30.52% lighter weight and 121.37% faster heat dissipation than unoptimized one.

The state of art multidisciplinary optimization featured with structural and material optimization attributes can deliberately meet medical necessity for performance-oriented orthotic devices.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

In real life, excitations are highly non-stationary in frequency and amplitude, which easily induces resonant vibration to structural responses. Conventional control algorithms in this case cannot guarantee cost-effective control effort and efficient structural response alleviation. To this end, this paper proposes a novel adaptive linear quadratic regulator (LQR) by integrating wavelet transform and genetic algorithm (GA).

In each time interval, multiresolution analysis of real-time structural responses returns filtered time signals dominated by different frequency bands. Minimization of cost function in each frequency band obtains control law and gain matrix that depend on temporal-frequency band, so suppressing resonance-induced filtered response signal can be directly achieved by regulating gain matrix in the temporal-frequency band, leading to emphasizing cost-function weights on control and state. To efficiently subdivide gain matrices in resonant and normal frequency bands, the cost-function weights are optimized by a developed procedure associated to genetic algorithm. Single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) structures subjected to near- and far-fault ground motions are studied.

Resonant band requires a larger control force than non-resonant band to decay resonance-induced peak responses. The time-varying cost-function weights generate control force more cost-effective than time-invariant ones. The scheme outperforms existing control algorithms and attains the trade-off between response suppression and control force under non-stationary excitations.

Proposed control law allocates control force amounts depending upon resonant or non-resonant band in each time interval. Cost-function weights and wavelet decomposition level are formulated in an elegant manner. Genetic algorithm-based optimization cost-efficiently results in minimizing structural responses.

This study aims to investigate the tendency that Malaysian consumers will choose the recombinant collagen-like protein (RCLP) from bacteria as an alternative source of collagen in their consumption and the determinants of the consumer acceptance.

Quantitative approach is adopted in the study. Descriptive analysis and logistic regression are used to analyze primary data collected from a survey.

The likelihood of consumers choosing RCLP as an alternative source of collagen is higher among elderly and females. The choice is significantly influenced by the idea that the collagen should support maqasid al-syariah, approved by national Islamic body, should clear on the ingredients used and could boost local economic activities in the future.

An ethical halal policy should be outlined as the guiding principles to the potential producers of RCLP.

An alternative source of collagen using bacteria as proposed is not yet being introduced in Malaysian industry, and the analysis on probability that consumers will accept this new sourced collagen product is using primary data from survey.

The long-span continuous rigid-frame bridges are commonly constructed by the section-by-section symmetrical balance suspension casting method. The deflection of these bridges is increasing over time. Wet joints are a typical construction feature of continuous rigid-frame bridges and will affect their integrity. To investigate the sensitivity of shear surface quality on the mechanical properties of long-span prestressed continuous rigid-frame bridges, a large serviced bridge is selected for analysis.

Its shear surface is examined and classified using the damage measuring method, and four levels are determined statistically based on the core sample integrity, cracking length and cracking depth. Based on the shear-friction theory of the shear surface, a 3D solid element-based finite element model of the selected bridge is established, taking into account factors such as damage location, damage number and damage of the shear surface. The simulated results on the stress distribution of the local segment, the shear surface opening and the beam deflection are extracted and analyzed.

The findings indicate that the main factors affecting the ultimate shear stress and shear strength of the shear surface are size, shear reinforcements, normal stress and friction performance of the shear surface. The connection strength of a single or a few shear surfaces decreases but with little effect on the local stress. Cracking and opening mainly occur at the 1/4 span. Compared with the rigid “Tie” connection, the mid-span deflection of the main span increases by 25.03% and the relative deflection of the section near the shear surface increases by 99.89%. However, when there are penetrating cracks and openings in the shear surface at the 1/2 span, compared with the 1/4 span position, the mid-span deflection of the main span and the relative deflection of the cross-section increase by 4.50%. The deflection of the main span increases with the failure of the shear surface.

These conclusions can guide the analysis of deflection development in long-span prestressed continuous rigid-frame bridges.