Hybrid application to BIM has been designed to reduce the risk of injuries and loss of life from personnel working in confined spaces

Building Information Modelling (BIM) is an intelligent 3D based model process that provides architecture, engineering and construction professionals the tools and understanding to plan, design, construct and manage building and infrastructure in a more efficient manner. In order to address environmental hazards associated with working in buildings, the BIM technology is rapidly evolving to coalesce with other emerging technologies such as wireless sensor motes (WSM). 

The School of Engineering and Built Environment of The Birmingham City University and other universities of Lahore and Hong Kong carried out research to further develop a hybrid application programming interface (API) plug-in to BIM. The research relied on the participation of our current BIM Coordinator, Erika Parn. To read the publication click here.

The application called “CosMoS” was originally designed as a system to monitor oxygen and temperature changes for remote sensing of spaces. In its second generation, “CoSMoS” was expanded. The researchers used archived records that proactively learn from data generated from WSN sensors (also known as nodes) that provide real-time monitoring of physical or environmental conditions during the building’s operations and maintenance (O&M) phase of asset management (AM).

The purpose of the system is to enable remote monitoring of confined spaces prior to conducting maintenance. The prototype is hoped to address health and safety issues related to working in confined spaces which frequently results in injury and/or loss of life. CoSMoS prototype has automated new safety applications for Facilities Management (FM) during the asset life-cycle and maintenance phase of a building’s O&M phase of AM. The application allows integrating, for instance, an additional layer of protection to attenuate human acts, errors or omissions that may occur when implementing risk control mitigation strategies.

Further development of CoSMoS presents a significant opportunity. Machine learning algorithms can be applied to develop self-learning and self-improving algorithms to automate predictions for members of the Facility Management team. Lessons learnt from existing buildings can be considered to influence future design developments.  CoSMoS could also contemplate the use of technological innovations such as miniaturisation and mass-manufacture of electronic componentry and create hybrid solutions that not only encapsulate a single building but also smart cities and entire economies.

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Exergy Analysis applied to a Power to Gas Plant

Exergy Analysis applied to a Power to Gas Plant

The share of Renewable Energy Sources (RES) for the European power-generation sector has almost reached 30%. Despite that, in the heating and cooling sectors only 20% comes from RES and in the transport sector, 7% was just exceeded in 2016.

In order to enable higher RES penetration, future energy systems would require further development of relevant infrastructures. Many strategies and technologies are being applied and developed and as a new integral and promising approach, power-to-x (PtX) technologies have attracted more supporters since they not only serve for demand-side management and energy storage but also facilitate the substitution of fossil fuels in the sectors of building, industry and transport.

Nevertheless, these systems are known for high capital costs and low roundtrip efficiencies. The system performance depends on the operating point of the electrolyser and system design, particularly the heat exchanger network.

To understand how the system performance is improved from one design to another, component-based exergy analysis can be employed. This will identify the sources and magnitude of the thermodynamic inefficiencies occurring with each component, highlights the components with the highest inefficiencies, and pinpoints the directions for system improvement.


In this paper, we investigate a Solid-Oxide Electrolyzer (SOE) based PtM plant with a fixed-bed catalytic methanator and a membrane module for methane upgrading. We employed a top-down approach to providing optimal system designs step by step from the system concept to optimal conceptual designs. Furthermore, we carried out an exergy evaluation to the system designs in order to understand how exergy dissipation and performance of the overall system and each component vary from one to another.

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