Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system can be divided and allocated to different sources of uncertainty in its inputs. This involves estimating sensitivity indices that quantify the influence of an input or group of inputs on the output. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem.
Modelica is an object-oriented, declarative, multi-domain modeling language for component-oriented modeling of complex systems, e.g., systems containing mechanical, electrical, electronic, hydraulic, thermal, control, electric power or process-oriented subcomponents. The free Modelica language is developed by the non-profit Modelica Association. The Modelica Association also develops the free Modelica Standard Library that contains about 1400 generic model components and 1200 functions in various domains, as of version 4.0.0.
Building science is the science and technology-driven collection of knowledge in order to provide better indoor environmental quality (IEQ), energy-efficient built environments, and occupant comfort and satisfaction. Building physics, architectural science, and applied physics are terms used for the knowledge domain that overlaps with building science. In building science, the methods used in natural and hard sciences are widely applied, which may include controlled and quasi-experiments, randomized control, physical measurements, remote sensing, and simulations. On the other hand, methods from social and soft sciences, such as case study, interviews & focus group, observational method, surveys, and experience sampling, are also widely used in building science to understand occupant satisfaction, comfort, and experiences by acquiring qualitative data. One of the recent trends in building science is a combination of the two different methods. For instance, it is widely known that occupants' thermal sensation and comfort may vary depending on their sex, age, emotion, experiences, etc. even in the same indoor environment. Despite the advancement in data extraction and collection technology in building science, objective measurements alone can hardly represent occupants' state of mind such as comfort and preference. Therefore, researchers are trying to measure both physical contexts and understand human responses to figure out complex interrelationships.
The HBV hydrology model, or Hydrologiska Byråns Vattenbalansavdelning model, is a computer simulation used to analyze river discharge and water pollution. Developed originally for use in Scandinavia, this hydrological transport model has also been applied in a large number of catchments on most continents.
A surrogate model is an engineering method used when an outcome of interest cannot be easily measured or computed, so an approximate mathematical model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as a function of design variables. For example, in order to find the optimal airfoil shape for an aircraft wing, an engineer simulates the airflow around the wing for different shape variables. For many real-world problems, however, a single simulation can take many minutes, hours, or even days to complete. As a result, routine tasks such as design optimization, design space exploration, sensitivity analysis and "what-if" analysis become impossible since they require thousands or even millions of simulation evaluations.
Thermal comfort is the condition of mind that expresses subjective satisfaction with the thermal environment. The human body can be viewed as a heat engine where food is the input energy. The human body will release excess heat into the environment, so the body can continue to operate. The heat transfer is proportional to temperature difference. In cold environments, the body loses more heat to the environment and in hot environments the body does not release enough heat. Both the hot and cold scenarios lead to discomfort. Maintaining this standard of thermal comfort for occupants of buildings or other enclosures is one of the important goals of HVAC design engineers.
Dymola is a commercial modeling and simulation environment based on the open Modelica modeling language.
SimulationX is a CAE software application running on Microsoft Windows for the physical simulation of technical systems. It is developed and sold by ESI Group.
OptiY is a design environment software that provides modern optimization strategies and state of the art probabilistic algorithms for uncertainty, reliability, robustness, sensitivity analysis, data-mining and meta-modeling.
Underfloor air distribution (UFAD) is an air distribution strategy for providing ventilation and space conditioning in buildings as part of the design of a HVAC system. UFAD systems use an underfloor supply plenum located between the structural concrete slab and a raised floor system to supply conditioned air to supply outlets, located at or near floor level within the occupied space. Air returns from the room at ceiling level or the maximum allowable height above the occupied zone.
Ecolego is a simulation software tool that is used for creating dynamic models and performing deterministic and probabilistic simulations. It is also used for conducting risk assessments of complex dynamic systems evolving over time.
Simcenter Amesim is a commercial simulation software for the modeling and analysis of multi-domain systems. It is part of systems engineering domain and falls into the mechatronic engineering field.
The detailed design of buildings needs to take into account various external factors, which may be subject to uncertainties. Among these factors are prevailing weather and climate; the properties of the materials used and the standard of workmanship; and the behaviour of occupants of the building. Several studies have indicated that it is the behavioural factors that are the most important among these. Methods have been developed to estimate the extent of variability in these factors and the resulting need to take this variability into account at the design stage.
Building performance simulation (BPS) is the replication of aspects of building performance using a computer-based, mathematical model created on the basis of fundamental physical principles and sound engineering practice. The objective of building performance simulation is the quantification of aspects of building performance which are relevant to the design, construction, operation and control of buildings. Building performance simulation has various sub-domains; most prominent are thermal simulation, lighting simulation, acoustical simulation and air flow simulation. Most building performance simulation is based on the use of bespoke simulation software. Building performance simulation itself is a field within the wider realm of scientific computing.
A building-energy performance gap is a disparity between the energy consumption predicted in the design stage of a building and the energy use in actual operation. It can have many causes.
A performance gap is a disparity that is found between the energy use predicted and carbon emissions in the design stage of buildings and the energy use of those buildings in operation. Research in the UK suggests that actual carbon emissions from new homes can be 2.5 times the design estimates, on average. For non-domestic buildings, the gap is even higher - actual carbon emissions as much as 3.8 times the design estimates, on average.
System-level simulation (SLS) is a collection of practical methods used in the field of systems engineering, in order to simulate, with a computer, the global behavior of large cyber-physical systems.
IDA IndoorClimate andEnergy is a Building performance simulation (BPS) software. IDA ICE is a simulation application for the multi-zonal and dynamic study of indoor climate phenomena as well as energy use. The implemented models are state of the art, many studies show that simulation results and measured data compare well.
