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Current efforts to improve building envelopes mostly focus on reducing energy demand by static measures such as insulation, selective glazing and shading. The resulting envelopes are limited in adapting to weather conditions or occupants’ needs and leave vast potentials for energy savings, onsite energy generation and improvement of occupant comfort untapped. In this work, we report on a dynamic building envelope that utilizes lightweight modules based on a hybrid hard/soft-material actuator to actively modulate solar radiation for local energy generation, passive heating, shading and daylight penetration. We describe two envelope prototypes and demonstrate autonomous solar tracking in real weather conditions. The dynamic photovoltaic envelope achieves an increase of up to 50% in electricity gains as compared to a static photovoltaic envelope. We assess energy savings potentials for three locations, six construction periods and two building use types. The envelope is most effective in temperate and arid climates, in which, for the cases analyzed, it can provide up to 115% of the net energy demand of an office room. Improvements in building envelope performance and onsite power generation are key to enabling zero-energy buildings. Here, Svetozarevic et al. present an adaptive solar facade driven by soft robotic solar trackers that allow both the modulation of daylight penetration and energy generation.

Aim: We propose a method for screening full blood count metadata for evidence of communicable and noncommunicable diseases using machine learning (ML). Materials & methods: High dimensional hematology metadata was extracted over an 11-month period from Sysmex hematology analyzers from 43,761 patients. Predictive models for age, sex and individuality were developed to demonstrate the personalized nature of hematology data. Both numeric and raw flow cytometry data were used for both supervised and unsupervised ML to predict the presence of pneumonia, urinary tract infection and COVID-19. Heart failure was used as an objective to prove method generalizability. Results: Chronological age was predicted by a deep neural network with R2: 0.59; mean absolute error: 12; sex with AUROC: 0.83, phi: 0.47; individuality with 99.7% accuracy, phi: 0.97; pneumonia with AUROC: 0.74, sensitivity 58%, specificity 79%, 95% CI: 0.73–0.75, p < 0.0001; urinary tract infection AUROC: 0.68, sensitivity 52%, specificity 79%, 95% CI: 0.67–0.68, p < 0.0001; COVID-19 AUROC: 0.8, sensitivity 82%, specificity 75%, 95% CI: 0.79–0.8, p = 0.0006; and heart failure area under the receiver operator curve (AUROC): 0.78, sensitivity 72%, specificity 72%, 95% CI: 0.77–0.78; p < 0.0001. Conclusion: ML applied to hematology data could predict communicable and noncommunicable diseases, both at local and global levels., Lay abstract Identifying and monitoring an infectious disease within a community requires sampling of both symptomatic and asymptomatic individuals. Hematology data from a full blood count contains significantly more information than used clinically. We applied machine learning to hematology data to predict the presence of both communicable and noncommunicable diseases.

Actively controlled building facade technologies provide an intriguing method for building energy and comfort management as well as on-site electricity generation. Here, a novel concept is proposed which allows for energy and comfort management on a multi-building level by making use of sunlight redirection via adaptive reflective panels mounted on a building facade. Utilizing such a system to share solar radiation between building surfaces will improve utilization of the solar resource in urban settings, contributing to a reduction in waste energy and subsequently mitigating the urban heat island effect. The authors term this technology a reflective adaptive solar facade. A framework is presented that models and assesses the performance of such a system, consisting of a Resistance-Capacitance building energy model coupled to a Monte Carlo ray tracing simulation. This framework is then utilized to determine the contribution of such a system to building energy savings. The simulation framework is applied to cases of different receiver designs including concentrating photovoltaic receivers and indirect heating. The facade's novel abilities to redistribute sunlight between buildings open new pathways for intelligent urban design via efficient distribution of solar energy resources.

The design of complex architectural components such as kinetic architectural elements poses a challenge due to the multiple technological branches involved. This paper presents a performative design environment that combines the branches of structural and energy engineering, control, industrial design, and architecture. The methodology is applied in the context of the Adaptive Solar Facade, a kinetic photovoltaic shading system for the HiLo building in Duebendorf, Switzerland. The authors describe how the environment enables the user to design the form of the facade, get feedback on its structural strength, analyse the energetic performance of the interior space, conduct a daylighting analysis, render images, and produce fabrication plans for a rapid design process. With the parametric design environment, project meetings transform from information exchanges to design sessions where all stakeholders can collaboratively influence the design and see immediate results. What would normally take a month, was condensed to just a few hours. Ultimately, this paper extends the field of performative design by presenting a practical example where a system as complex as a kinetic photovoltaic envelope can be designed, prototyped, and fabricated by a small team of four designers.

The utilisation of a dynamic photovoltaic system for adaptive shading can improve building energy performance by controlling solar heat gains and natural lighting, while simultaneously generating electricity on site. This paper firstly presents an integrated simulation framework to couple photovoltaic electricity generation to building energy savings through adaptive shading. A high-resolution radiance and photovoltaic model calculates the photovoltaic electricity yield while taking into account partial shading between modules. The remaining solar irradiation that penetrates the window is used in a resistance-capacitance building thermal model. A simulation of all possible dynamic configurations is conducted for each hourly time step, of which the most energy efficient configuration is chosen. We then utilise this framework to determine the optimal orientation of the photovoltaic panels to maximise the electricity generation while minimising the building’s heating, lighting and cooling demand. An existing adaptive photovoltaic facade was used as a case study for evaluation. Our results report a 20–80% net energy saving compared to an equivalent static photovoltaic shading system depending on the efficiency of the heating and cooling system. In some cases the Adaptive Solar Facade can almost compensate for the entire energy demand of the office space behind it. The control of photovoltaic production on the facade, simultaneously with the building energy demand, opens up new methods of building management as the facade can control both the production and consumption of electricity.

This paper presents research on lightweight construction and smart, integrated and adaptive building systems. The research is focused on addressing challenges related to the building industry at large, including most prominently the improvement of energy efficiency, onsite power generation, and the reduction of the quantity of materials required to build. We introduce four innovations in context of the design of an experimental building (NEST HiLo): a lightweight, unreinforced funicular floor system; a flexibly formed, concrete shell sandwich roof; a soft actuated, adaptive solar facade and an automated, occupant-centred control system. We demonstrate novel structural engineering approaches to compression-only concrete elements and shell design using multi-criteria shape optimisation. We explore a building facade concept, which employs robotic actuators for solar shading and on-site generation. In addition, the operational phase of the building will be used as a living laboratory where occupants' locations and needs for comfort are detected and used for the control of the energy innovations. The research provides insight into design topics that will become increasingly relevant for the evolution of improved lifecycle energy buildings.

Labelled human comfort data can be a valuable resource in optimising the built environment, and improving the wellbeing of individual occupants. The acquisition of labelled data however remains a challenge. This paper presents a methodology for the collection of in-situ occupant feedback data using a Fitbit smartwatch. The clock-face application cozie can be downloaded free-of-charge on the Fitbit store and tailored to fit a range of occupant comfort related experiments. In the initial trial of the app, fifteen users were given a smartwatch for one month and were prompted to give feedback on their thermal preferences. In one month, with minimal administrative overhead, 1460 labelled responses were collected. This paper demonstrates how these large data sets of human feedback can be analysed to reveal a range of results from building anomalies, occupant behaviour, occupant personality clustering, and general feedback related to the building. The paper also discusses limitations in the approach and the next phase of design of the platform.

We present an expansion of the psychrometric chart for thermal comfort analysis using a new contour shading method that demonstrates a wider range of potential comfort conditions through the incorporation of additional comfort parameters. These extra dimensions include mean radiant temperature, air movement, metabolic rate, skin wettedness and the transitional behavior of occupants. The representations allow us to think outside the thermal comfort box with the use of innovative thermal design and comfort feedback for occupants. Building on the Olgyay bioclimatic chart, allowing architects to “Design with Climate”, the new chart vizualizes a wide range of conditions that illustrate a physical basis for expanding comfort zones. It uses basic spatially invariant metrics employed in adaptive and other comfort models to allow "design with comfort" across all thermal comfort variables. The development of these methods has resulted in an open-source repository and web app available for designers and researchers to reproduce the charts and color-shading for their own projects.

This study describes a human-building interaction framework called the SDE Learning Trail, a mobile app that is currently deployed at the SDE4 building - the new Net Zero Energy Building (NZEB) at the National University of Singapore (NUS). This framework enables building occupants and visitors to learn about the well and green features of the new NZEB while facilitating collection of environmental comfort feedback in a simple and intuitive way. Within just three months, 1163 feedback responses of thermal, visual and aural comfort were obtained. A total of 616 participants have contributed to the study till date, with 79 participants who provided five or more instances of feedback. This data set provides new opportunities for understanding occupant comfort behavior through supervised and unsupervised data-driven methods. This paper demonstrates how occupants can be clustered into comfort personality types that could be used as a foundation for prediction and recommendation systems that use real-time occupant behavior instead of rigid comfort models. We provide an overview of the application methodology and initial results in the SDE4 building.

An adaptive solar facade can improve building energy performance by controlling solar heat gains and natural lighting, while simultaneously generating electricity on site. The adaptive control of the solar facade is determined through an optimisation algorithm that minimises the net energy demand. In this paper, we first evaluate the sensitivity of the adaptive solar facade to the thermal performance of the building envelope for a south facing room in Zurich. We then evaluate the performance of an adaptive solar facade on 11 building use types spanning six construction periods. In addition, we compare the performance of an adaptive system against an equivalent static photovoltaic system, and a facade with no shading system. Our results show that the adaptive solar facade performs best in buildings that have a high cooling demand and low heating demand. This is because the optimum configurations for cooling minimisation generate the maximum photovoltaic electricity. As a result, we notice a higher energy saving potential in newer buildings with low envelope thermal transmittance (U-value or infiltration). However, in buildings with a very high cooling demand, and no heating demand, there is only a small improvement in performance compared to an equivalent static system. An adaptive solar facade is therefore an optimum solution when there are both heating demands, and cooling demands present. Modern offices, retail stores, food stores, and schools have this property and perform well with an adaptive solar facade compared to an equivalent static system, and a facade with no shading., Energy Procedia, 122, ISSN:1876-6102, CISBAT 2017 International Conference Future Buildings & Districts – Energy Efficiency from Nano to Urban Scale

This paper presents a case study of integrated sustainable building design in the tropics. In an interdisciplinary approach, we evaluated a series of strategies to increase the expected performance of a building prototype in the city of Barranquilla, Colombia. We created plausible architectural options, and used building performance simulation techniques to evaluate the feasibility of energy and water efficiency strategies. The aim was to develop close to optimal solutions to minimize the use of resources in the building while assuring high standards of comfort, an attractive return on investment, and an appealing architectural expression. As a result, four strategic bundles or sustainability concepts were seamlessly integrated into the architecture of the building. In comparison with a local school, the building achieves up to 93% of net energy savings and related emissions, 86% of water savings, and COP 144.5 million (USD 76,891.34) of yearly economic savings with a payback time period of 7.4 years. The results of this integrated approach successfully address the three pillars of sustainable development (i.e. social, economic and environmental) at the building scale and represent an exemplary case for the upcoming Colombian Green Building Code.

A powerful replica molding methodology to transfer on-demand functional topographies to the surface of bacterial cellulose nanofiber textures is presented. With this method, termed guided assembly-based biolithography (GAB), a surface-structured polydimethylsiloxane (PDMS) mold is introduced at the gas-liquid interface of an Acetobacter xylinum culture. Upon bacterial fermentation, the generated bacterial cellulose nanofibers are assembled in a three-dimensional network reproducing the geometric shape imposed by the mold. Additionally, GAB yields directional alignment of individual nanofibers and memory of the transferred geometrical features upon dehydration and rehydration of the substrates. Scanning electron and atomic force microscopy are used to establish the good fidelity of this facile and affordable method. Interaction of surface-structured bacterial cellulose substrates with human fibroblasts and keratinocytes illustrates the efficient control of cellular activities which are fundamental in skin wound healing and tissue regeneration. The deployment of surface-structured bacterial cellulose substrates in model animals as skin wound dressing or body implant further proves the high durability and low inflammatory response to the material over a period of 21 days, demonstrating beneficial effects of surface structure on skin regeneration.