ABSTRACT Recently, the integration between healthcare services and new technologies has been enhanced to be very necessary and effective inside digital Hospitals. Digital hospitals include a huge number of healthcare advanced technologies that have special digital and architectural requirement; these requirements cannot be provided in traditional hospitals. Many previous studies and guidelines addressed few numbers of digital hospital’s rooms and their architectural requirements. Hence, in this study, healthcare advanced technologies has been determined for outlining the architectural consideration of digital hospital’s rooms. Accordingly, Robotic Surgery Ward (RSW) has been compared with Traditional Surgery Ward (TSW) for: a) demonstrating the effect of an advanced technology (Robotic technology) on a digital hospital ward and b) helping designers to find out the main architectural and economic principles of designing RSWs besides TSWs. The main findings in this study are: a) outlining the main architectural characteristics of digital hospitals in general and digital hospital’s rooms in specific, b) articulating the main architectural and economic aspects for RSW and robotic surgery rooms, which is different from TSW. As an application of the comparative analyses, possible design alternatives of RSW and TSW has been also proposed and compared.

ABSTRACT Recently, the automation of architectural design process has been focused specifically in Healthcare buildings (HCB) for easier implementation and faster feedback. Hence, a great evolution of Computational Implementations (CIs) were appeared and studied for early stages of design process of HCB, such as generating design solutions, evaluation of design solutions or others to provide helpful tools for designers. This paper provides comparative analyses of a set of CIs that can be applied on different architectural design stages in HCB, these stages includes: a) architectural programming and topological diagram, b) generating design alternatives and c) evaluation of design solutions. The focused CIs in this study have been classified to computational tools, computational algorithms, computational approaches and hybrid methods; they are compared using a set of criteria with various evaluation methods. This comparative analysis helps designers to determine the appropriate CI or CIs’ combinations for each main early stage of HCB design, and also the possibilities of connecting two of the studied CIs in a framework to get wider outcomes were studied. The main study findings are the capabilities, limitation and features of each CI, in addition to the best selections in each early stage for different HCB design cases. Also, possible connections between different CIs were discussed on simple examples as a fruitful outcome of analyzing CIs’ combinations.

Recently, the automation of architectural design process has been focused specifically in Healthcare buildings (HCB) for easier implementation and faster feedback. Hence, a great evolution of Computational Implementations (CIs) were appeared and studied for early stages of design process of HCB, such as generating design solutions, evaluation of design solutions or others to provide helpful tools for designers. This paper provides comparative analyses of a set of CIs that can be applied on different architectural design stages in HCB, these stages includes: a) architectural programming and topological diagram, b) generating design alternatives and c) evaluation of design solutions. The focused CIs in this study have been classified to computational tools, computational algorithms, computational approaches and hybrid methods; they are compared using a set of criteria with various evaluation methods. This comparative analysis helps designers to determine the appropriate CI or CIs’ combinations for each main early stage of HCB design, and also the possibilities of connecting two of the studied CIs in a framework to get wider outcomes were studied. The main study findings are the capabilities, limitation and features of each CI, in addition to the best selections in each early stage for different HCB design cases. Also, possible connections between different CIs were discussed on simple examples as a fruitful outcome of analyzing CIs’ combinations.

ABSTRACT Recently, the automation of architectural design process has been focused specifically in Healthcare buildings (HCB) for easier implementation and faster feedback. Hence, a great evolution of Computational Implementations (CIs) were appeared and studied for early stages of design process of HCB, such as generating design solutions, evaluation of design solutions or others to provide helpful tools for designers. This paper provides comparative analyses of a set of CIs that can be applied on different architectural design stages in HCB, these stages includes: a) architectural programming and topological diagram, b) generating design alternatives and c) evaluation of design solutions. The focused CIs in this study have been classified to computational tools, computational algorithms, computational approaches and hybrid methods; they are compared using a set of criteria with various evaluation methods. This comparative analysis helps designers to determine the appropriate CI or CIs’ combinations for each main early stage of HCB design, and also the possibilities of connecting two of the studied CIs in a framework to get wider outcomes were studied. The main study findings are the capabilities, limitation and features of each CI, in addition to the best selections in each early stage for different HCB design cases. Also, possible connections between different CIs were discussed on simple examples as a fruitful outcome of analyzing CIs’ combinations.

Abstract Robotic surgery is one of the most recent technologies in healthcare building field. Due to the design complexity of Robotic surgery wards, computational implementations are being developed to either measure the effect of inserting advanced technologies as Electronic medical recorders and tele surgery, or evaluate design alternatives on health-care building. This paper presents a design framework that responds to the need for coordinating design phases for Robotic Surgery Wards (RSWs) computationally. This proposed design framework for RSWs can generate functional RSW alternatives and more than one solution for each alternative. The framework has been structured based on the main architectural considerations of RSWs which are geometric and topological, the economic considerations, specific developed pools for shape and corridor patterns, and the theory of “Shape Grammars"has been utilized to compute the framework to generate a vast number of design alternatives. Accordingly, a computational implementation has been established to assist designers in early design stages. Numerical validation for the applications of the developed framework and implementation has been conducted by using reference examples of RSWs. The main finding in this paper is providing healthcare building designers with a computational implementation that generates RSW alternative computationally based on specific shape and cost levels.

Abstract Robotic surgery is one of the most recent technologies in healthcare building field. Due to the design complexity of Robotic surgery wards, computational implementations are being developed to either measure the effect of inserting advanced technologies as Electronic medical recorders and tele surgery, or evaluate design alternatives on health-care building. This paper presents a design framework that responds to the need for coordinating design phases for Robotic Surgery Wards (RSWs) computationally. This proposed design framework for RSWs can generate functional RSW alternatives and more than one solution for each alternative. The framework has been structured based on the main architectural considerations of RSWs which are geometric and topological, the economic considerations, specific developed pools for shape and corridor patterns, and the theory of “Shape Grammars"has been utilized to compute the framework to generate a vast number of design alternatives. Accordingly, a computational implementation has been established to assist designers in early design stages. Numerical validation for the applications of the developed framework and implementation has been conducted by using reference examples of RSWs. The main finding in this paper is providing healthcare building designers with a computational implementation that generates RSW alternative computationally based on specific shape and cost levels.

Herein, the design of nanocomposite (NC) formulations that consist of metal enzyme cofactors, highly conductive carbon materials, DIET activators, to boost AD biogas production from anaerobically incubated cattle manure are investigated and discussed. Three different NC formulations were designed and synthesized: zinc ferrite (ZnFe), ZnFe with 10% carbon nanotubes (ZFCNTs), and zinc ferrite with 10% C76 fullerene (ZFC76). The structure and morphology of the nano-additives were investigated via x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive x-ray (EDX), and transmission electron microscopy (TEM). NCs were supplemented to lab-scale biodigesters containing organic slurry. Biogas production was monitored daily and compared to blank biodigesters for 50 days. The maximum methane enhancement was obtained for ZnFe, which promoted methane production to 185.3%. ZFCNTs and ZFC76 showed a positive impact on the hydraulic retention time and enhanced methane production to 162% and 145.9%, respectively compared to the blank reactors.

Herein, the design of nanocomposite (NC) formulations that consist of metal enzyme cofactors, highly conductive carbon materials, DIET activators, to boost AD biogas production from anaerobically incubated cattle manure are investigated and discussed. Three different NC formulations were designed and synthesized: zinc ferrite (ZnFe), ZnFe with 10% carbon nanotubes (ZFCNTs), and zinc ferrite with 10% C76 fullerene (ZFC76). The structure and morphology of the nano-additives were investigated via x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive x-ray (EDX), and transmission electron microscopy (TEM). NCs were supplemented to lab-scale biodigesters containing organic slurry. Biogas production was monitored daily and compared to blank biodigesters for 50 days. The maximum methane enhancement was obtained for ZnFe, which promoted methane production to 185.3%. ZFCNTs and ZFC76 showed a positive impact on the hydraulic retention time and enhanced methane production to 162% and 145.9%, respectively compared to the blank reactors.

Herein, the design of nanocomposite (NC) formulations that consist of metal enzyme cofactors, highly conductive carbon materials, DIET activators, to boost AD biogas production from anaerobically incubated cattle manure are investigated and discussed. Three different NC formulations were designed and synthesized: zinc ferrite (ZnFe), ZnFe with 10% carbon nanotubes (ZFCNTs), and zinc ferrite with 10% C76 fullerene (ZFC76). The structure and morphology of the nano-additives were investigated via x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive x-ray (EDX), and transmission electron microscopy (TEM). NCs were supplemented to lab-scale biodigesters containing organic slurry. Biogas production was monitored daily and compared to blank biodigesters for 50 days. The maximum methane enhancement was obtained for ZnFe, which promoted methane production to 185.3%. ZFCNTs and ZFC76 showed a positive impact on the hydraulic retention time and enhanced methane production to 162% and 145.9%, respectively compared to the blank reactors.

Herein, the design of nanocomposite (NC) formulations that consist of metal enzyme cofactors, highly conductive carbon materials, DIET activators, to boost AD biogas production from anaerobically incubated cattle manure are investigated and discussed. Three different NC formulations were designed and synthesized: zinc ferrite (ZnFe), ZnFe with 10% carbon nanotubes (ZFCNTs), and zinc ferrite with 10% C76 fullerene (ZFC76). The structure and morphology of the nano-additives were investigated via x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive x-ray (EDX), and transmission electron microscopy (TEM). NCs were supplemented to lab-scale biodigesters containing organic slurry. Biogas production was monitored daily and compared to blank biodigesters for 50 days. The maximum methane enhancement was obtained for ZnFe, which promoted methane production to 185.3%. ZFCNTs and ZFC76 showed a positive impact on the hydraulic retention time and enhanced methane production to 162% and 145.9%, respectively compared to the blank reactors.