Constructing lunar bases is crucial as lunar missions progress towards utilization and exploitation. The challenging lunar environment, with its unique characteristics and limited resources, requires special materials, structures, and construction methods. Inflatable structures offer great potential for lunar construction due to their advantages in transportation, stowage, construction, and reliability. This paper proposes a rigidizable inflatable lunar habitat that maintains its shape even after air leakage, enhancing safety, durability, and fixability. The membrane material adapts to different requirements during transportation, construction, and service, achieved through solid-state actuation of shape memory polymer (SMP) for stiffness variation, allowing multiple moves and ground tests. This work comprises three parts: 1) system: design concept and construction processes, 2) material: design and characterization of restraint and rigidization materials, and 3) structure: numerical validation of structure properties. Finite element analysis, based on material models obtained through dynamic mechanical analysis (DMA) and tensile tests, demonstrates the effectiveness of including an SMP rigidization layer in preventing collapse and enhancing dynamic properties. This paper not only proposes a new system, but also provides material design methods and requirements, along with structural validation techniques. Findings validate the feasibility of rigidizable inflatable lunar habitats, applicable in extreme environments, also in temporary buildings, space structures, and soft robotics.

Conventional hinge actuators often face limitations including excessive weight, large size and unpleasant noise. Shape memory alloys (SMAs) offer a solution to address these issues due to their favorable characteristics, such as lightweight, high actuation force and small form factor. However, most existing SMA-based hinge actuators rely on the tension loading mode. Achieving an ideal actuation angle thereby necessitates the inclusion of long SMA wires, which inadvertently constrains the actuator size. Notably, the full potential of SMAs’ deformation capacities, encompassing torsion and bending, remains largely untapped and underutilized. In this research, a reversible torsion SMA hinge actuator is studied, which can reversibly open 60° during heating and cooling. The actuator weighs 2 g, and can produce actuation forces of up to 5 N. The mechanical performances of nitinol at different temperatures are measured. Based on the measurements, a model which can predict the opening and closing angle is proposed, with deviations of 13.5 ± 8.2 %. Gripper and butterfly demonstrators constructed by the hinge actuators are given as application examples. The actuators hold potential in many fields like soft robotics, aerospace and medical instruments.

The paper explores the potential applications of adaptive components based on shape memory polymer (SMP) composites in vibration control of plate/shell structures and rigidization of inflatable structures. These components achieve stiffness and damping variation by thermally actuating SMP between its glassy and rubbery states. In CASE A, steel-SMP sandwich plates of a truss bridge are actuated to glass transition temperature (Tg), where material damping reaches the peak to mitigate dynamic responses. CASE B proposes a simple and reversible rigidization method for inflatable structures, creating high compaction ratio and design flexibility. Converting the SMP layer between its glassy and rubbery states, inflatable structures achieve multiple functions during transportation, construction, and service life. SMP-based adaptive components enhance structural performance and mitigate dynamic effects in demanding environments for various structures.

We developed a shape-changing constructive kit, named Mimosa1. A key component of the toolkit is the modular hinges, each of which is equipped with two antagonistic shape memory alloy (SMA) wires. One wire deforms the hinge to approach its predetermined angle at high temperature, and another wire drives the hinge back when it cools down. Hinge leaves are available in different materials including acrylic, cardboard and textile, which increases the versatility of the toolkit. Every hinge weighs 2.1-5.4 g, and generates up to 5.7 N actuation force. A Bluetooth control module was developed, enabling remote control of the shape-changing objects. Mimosa aims to inspire designers to explore and create interactive shape-morphing objects with SMAs. A few examples are given such as a gripper, a rolling robot, a butterfly, an airplane and a self-closing pocket. A workshop study with 6 participants showed that Mimosa indeed motivated and inspired the participants to create new ideas.

Sharing breathing signals has the capacity to provide insights into hidden experiences and enhance interpersonal communication. However, it remains unclear how the modality of breath signals (visual, haptic) is socially interpreted during collaborative tasks. In this mixed-methods study, we design and evaluate BreatheWithMe, a prototype for real-time sharing and receiving of breathing signals through visual, vibrotactile, or visual-vibrotactile modalities. In a within-subjects study (15 pairs), we investigated the effects of modality on breathing synchrony, social presence, and overall user experience. Key findings showed: (a) there were no significant effects of visualization modality on breathing synchrony, only on deliberate music-driven synchronization; (b) visual modality was preferred over vibrotactile feedback, despite no differences across social presence dimensions; (c) BreatheWithMe was perceived to be an insightful window into others, however included data exposure and social acceptability concerns. We contribute insights into the design of multi-modal real-time breathing visualization systems for colocated, collaborative tasks.

As an emerging technology, smart textiles have attracted attention for rehabilitation purposes or to monitor heart rate, blood pressure, breathing rate, body posture, as well as limb movements. Traditional rigid sensors do not always provide the desired level of comfort, flexibility, and adaptability. To improve this, recent research focuses on the development of textile-based sensors. In this study, knitted strain sensors that are linear up to 40% strain with a sensitivity of 1.19 and a low hysteresis characteristic were integrated into different versions of wearable finger sensors for rehabilitation purposes. The results showed that the different finger sensor versions have accurate responses to different angles of the index finger at relaxation, 45° and 90°. Additionally, the effect of spacer layer thickness between the finger and sensor was investigated.

Tailoring the order in hierarchical structures is a key goal of bioinspired nanocomposite design. Recently, nacre-like materials have been developed by solvent evaporation methods that are scalable and attain advanced functionalities. However, understanding the alignment mechanisms of 2D fillers, nanosheets, or platelets remains challenging. This work explores possible pathways for nanocomposite ordering via orientation distribution functions. We demonstrate how the immobilization of 2D materials via (pseudo)network formation is crucial to alignment based on evaporation. We show a modified affine deformation model that describes such evaporative methods. In this, a gel network develops enough yield stress and uniformly deforms as drying proceeds, along with the immobilized particles, causing an in-plane orientation. Herein, we tested the dominance of this approach by using a thermo-reversible gel for rapid montmorillonite (MMT) particle fixation. We researched gelatin/MMT as a model system to investigate the effects of high loadings, orientational order, and aspect ratio. The nacre-like nanocomposites showed a semiconstant order parameter (⟨P₂⟩ ∼ 0.7) over increasing nanofiller content up to 64 vol % filler. This remarkable alignment resulted in continuously improved mechanical and water vapor barrier properties over unusually large filler fractions. Some variations in stiffness and diffusion properties were observed, possibly correlated to the applied drying conditions of the hybrid hydrogels. The affine deformation strategy holds promise for developing next-generation advanced materials with tailored properties even at (very) high filler loadings. Furthermore, a gelling approach offers the advantages of simplicity and versatility in the formulation of the components, which is useful for large-scale fabrication methods.

As an emerging technology, smart textiles have attracted attention for rehabilitation purposes to monitor heart rate, blood pressure, breathing rate, body posture and limb movements. Compared with traditional sensors, knitted sensors constructed from conductive yarns are breathable, stretchable and washable, and therefore, provide more comfort to the body and can be used in everyday life. In this study, knitted strain sensors were produced that are linear with up to 40% strain, sensitivity of 1.19 and hysteresis of 1.2% in absolute values, and hysteresis of 0.03 when scaled to the working range of 40%. The developed sensor was integrated into a wearable wrist-glove system for finger and wrist monitoring. The results show that the wearable was able to detect different finger angles and positions of the wrist.

PURPOSE: For wheelchair users with a spinal cord injury, the lower body may be a more convenient cooling site than the upper body. However, it remains unknown if leg cooling reduces thermal strain in these individuals. We compared the impact of upper-body versus lower-body cooling on physiological and perceptual outcomes during submaximal arm-crank exercise under heat stress in individuals with paraplegia. METHODS: Twelve male participants with paraplegia (T4-L2, 50% complete lesion) performed a maximal exercise test in temperate conditions, and three heat stress tests (32°C, 40% relative humidity) in which they received upper-body cooling (COOL-UB), lower-body cooling (COOL-LB), or no cooling (CON) in a randomized counterbalanced order. Each heat stress test consisted of four exercise blocks of 15 min at 50% of peak power output, with 3 min of rest in between. Cooling was applied using water-perfused pads, with 14.8-m tubing in both COOL-UB and COOL-LB. RESULTS: Gastrointestinal temperature was 0.2°C (95% confidence interval (CI), 0.1°C to 0.3°C) lower during exercise in COOL-UB versus CON (37.5°C ± 0.4°C vs 37.7°C ± 0.3°C, P = 0.009), with no difference between COOL-LB and CON ( P = 1.0). Heart rate was lower in both COOL-UB (-7 bpm; 95% CI, -11 to -3 bpm; P = 0.01) and COOL-LB (-5 bpm; 95% CI, -9 to -1 bpm; P = 0.049) compared with CON. The skin temperature reduction at the cooled skin sites was larger in COOL-LB (-10.8°C ± 1.1°C) than in COOL-UB (-6.7°C ± 1.4°C, P < 0.001), which limited the cooling capacity in COOL-LB. Thermal sensation of the cooled skin sites was improved and overall thermal discomfort was lower in COOL-UB ( P = 0.01 and P = 0.04) but not in COOL-LB ( P = 0.17 and P = 0.59) compared with CON. CONCLUSIONS: Upper-body cooling more effectively reduced thermal strain than lower-body cooling in individuals with paraplegia, as it induced greater thermophysiological and perceptual benefits.

Devices delivering sophisticated and natural haptic feedback often encompass numerous mechanical elements, leading to increased sizes and wearability challenges. Shape memory alloys (SMAs) are lightweight, compact, and have high power-to-weight ratios, and thus can easily be embedded without affecting the overall device shapes. Here, a review of SMA-based haptic wearables is provided. The article starts with an introduction of SMAs, while incorporating analyses of relevant devices documented in the literature. Haptic and SMA materials fields are correlated, with haptic perception insights aiding SMA actuator design, and distinct SMA mechanisms offering diverse haptic feedback types. A design process for SMA haptic wearables is proposed based on material-centered approach. We show SMAs hold potential for haptic devices aiding visually impaired people and promise in immersive technology and remote interpersonal haptic communication.

Purpose: The purpose of this study is to analyze the question “In what order of magnitude does the comfort and performance improvement lie with the use of a cooling vest for construction workers?”. Design/methodology/approach: The use of personal cooling systems, in the form of cooling vests, is not only intended to reduce the heat load, in order to prevent disruption of the thermoregulation system of the body, but also to improve work performance. A calculation study was carried out on the basis of four validated mathematical models, namely a cooling vest model, a thermophysiological human model, a dynamic thermal sensation model and a performance loss model for construction workers. Findings: The use of a cooling vest has a significant beneficial effect on the thermal sensation and the loss of performance, depending on the thermal load on the body. Research limitations/implications: Each cooling vest can be characterized on the basis of the maximum cooling power (Pmax; in W/m²), the cooling capacity (Auc; in Wh/m2) and the time (tc; in minutes) after which the cooling power is negligible. In order to objectively compare cooling vests, a (preferably International and/or European) standard/guideline must be compiled to determine the cooling power and the cooling capacity of cooling vests. Practical implications: It is recommended to implement the use of cooling vests in the construction process so that employees can use them if necessary or desired. Social implications: Climate change, resulting in global warming, is one of the biggest problems of present times. Rising outdoor temperatures will continue in the 21st century, with a greater frequency and duration of heat waves. Some regions of the world are more affected than others. Europe is one of the regions of the world where rising global temperatures will adversely affect public health, especially that of the labor force, resulting in a decline in labor productivity. It will be clear that in many situations air conditioning is not an option because it does not provide sufficient cooling or it is a very expensive investment; for example, in the situation of construction work. In such a situation, personal cooling systems, such as cooling vests, can be an efficient and financially attractive solution to the problem of discomfort and heat stress. Originality/value: The value of the study lies in the link between four validated mathematical models, namely a cooling vest model, a thermophysiological human model, a dynamic thermal sensation model and a performance loss model for construction workers.

In this study, using construction activities as an example, a proposal is made for the time-dependent prediction of the thermal sensation and the performance loss using a cooling vest, under transient conditions. The approach presented here can, mutatis mutandis, be used for any work activity and the use of a cooling vest, whether or not in a building.

This paper has the objective to initiate a discussion on potential improvements or extension of the validity of the original equation of the Predicted Percentage of Dissatisfied (PPD), according to (NEN-)EN-ISO 7730. This paper is to be regarded as a supplement to a paper on a re-derivation of the PMV equation in the Fanger model (Roelofsen, Jansen, and Vink 2021). In practice, in scientific research it regularly appears that the PMV (Predicted Mean Vote), and by extension the PPD, are applied outside the range based on which the PMV and the PPD equation are derived. In practice, this can occur, for example, in the evaluation of the measurement or calculation of temperature exceedances in a room, for sedentary activities. As it turns out, a PMV equation with an application of −3 to 3, for at least sedentary activities, would be useful in the different fields of study. For that reason, Roelofsen has adapted the PMV equation in the (NEN-)EN-ISO model. But to what extent should the PPD equation also be adjusted? After all, the PPD is also derived from and limited to a PMV of −2 to 2, according to (NEN-)EN-ISO 7730.

Smart wearables are increasingly used to help people deal with stress. Still, a less explored area of research in this field concerns the partnerships that smart wearables can take on when engaging people in stress-coping activities. To facilitate further understanding of the human-wearable partnerships, we designed Grippy, a smart wearable system composed of a physical glove and a smartphone application to help the wearer actively explore and cope with stress in daily situations. We introduced Grippy, as a speculative probe, to six participants (four master students and two university employees) who wore it for five successive days. Participants were interviewed about their use experience of Grippy during and after these five days. Qualitative data collected from the interviews was interpreted regarding how Grippy could fit into people’s stress-coping activities across different daily contexts and what kinds of partnerships with the smart wearable were perceived by the participants. In addition, we reflect on the design issues that led to the mismatch between our design intentions and people’s actual use experiences. We discuss how these results have deepened our understanding of human-wearable partnerships in the context of stress management and the usability issues that might hinder the expression and acceptance of smart wearables designed as partners. We end the discussion by reflecting on the implications of smart wearables as partners in mental healthcare.

Objectives To evaluate how separate and combined climatic parameters affect peak core temperature during exercise in the heat using computer simulations fed with individual data. Methods The impact of eight environmental conditions on rectal temperature (T re) was determined for exercise under heat stress using the Fiala-thermal-Physiology-and-Comfort simulation model. Variations in ambient temperature (T a ±6°C), relative humidity (RH±15%) and solar radiation (SR+921 W/m 2) were assessed in isolation and combination (worst-case/best-case scenarios) and compared with baseline (T a 32°C, RH 75%, SR 0 W/m 2). The simulation model was fed with personal, anthropometric and individual exercise characteristics. Results 54 athletes exercised for 46±10 min at baseline conditions and achieved a peak core temperature of 38.9±0.5°C. Simulations at a higher T a (38°C) and SR (921 W/m 2) resulted in a higher peak T re compared with baseline (+0.6±0.3°C and +0.5±0.2°C, respectively), whereas a higher RH (90%) hardly affected peak T re (+0.1±0.1°C). A lower T a (26°C) and RH (60%) reduced peak T re by-0.4±0.2°C and a minor-0.1±0.1°C, respectively. The worst-case simulation yielded a 1.5±0.4°C higher T re than baseline and 2.0±0.7°C higher than the best-case condition. Conclusion Combined unfavourable climatic conditions produce a greater increase in peak core temperature than the sum of its parts in elite athletes exercising in the heat.

Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we investigated the possibility to extract these statistics from acceleration sensor data generated by a previously developed sensor garment. We used deep learning-based models to recognize five football-related activities (jogging, sprinting, passing, shooting and jumping) in an accurate, robust, and fast manner. A combination of convolutional (CNN) layers followed by recurrent (bidirectional) LSTM layers achieved up to 98.3% of accuracy. Our results showed that deep learning models performed better in evaluation time and prediction accuracy than traditional machine learning algorithms. In addition to an increase in accuracy, the proposed deep learning architecture showed to be 2.7 to 3.4 times faster in evaluation time than traditional machine learning methods. This demonstrated that deep learning models are accurate as well as time-efficient and are thus highly suitable for cost-effective, fast, and accurate human activity recognition tasks.