Environmental Control System Research Articles

Comfort and Economic Viability of Personal Ceiling Fans Assisted by Night Ventilation in a Renovated Office Building

An expected increase in the use of air conditioning by 2050 will significantly increase electricity demand and come at a cost to the environment. Implementing passive cooling strategies and focusing on personal environmental control systems (PECSs) could help to address this issue. While numerous studies have investigated the positive impact of PECSs on thermal comfort and energy savings, their overall economic benefit has been poorly addressed. We present an economic evaluation of personal fans for an office building in Germany. Building performance simulation was used to compare passive and active cooling concepts, and sensitivity analysis was performed for different climate scenarios. A cost-benefit analysis was carried out, including an assessment of investment and operating costs and the monetary value of relative performance. The transferability of comfort and productivity into costs is the novelty of this paper. The results showed that by supplementing night ventilation with personal fans, discomfort hours could be reduced by up to 50%. However, the initial investment of the fan is not compensated by savings in productivity losses compared to night ventilation alone. A reduction in the cost of the technology could help to economically offset the investment. The results contribute to the literature on the economic evaluation of a PECS by proposing a framework to motivate its implementation in buildings.

The Potential of Using Vortex Tube to Ameliorate Aircraft Environmental Control System

This paper proposes a new air cycle system by replacing the turbine assembly with vortex tubes and a parameter-matching method independent of the architecture of the air cycle system. Only, in terms of refrigerating and dehumidification, the performance of the newly proposed vortex system is worse than that of a conventional air cycle system under the same bleed air parameters. However, for aircraft practical applications, the overall performance of air cycle systems requires additional considerations such as the heating capacity, weight of the system, and extra aviation fuel used to transport that weight. Therefore, this paper conducts an integrated performance comparison between the new system and a conventional system based on the overall fuel mass penalty criterion. The results show that whether the new system has a smaller total takeoff mass depends on the bleed air parameters, flight duration, and flight speed. For specific bleed air parameters, there is a specific R=1 curve where the new system and the turbine system have the same total takeoff mass. The performance of the new system is better than that of the turbine system only when the values of flight Mach number and flight duration are at the lower left of the R=1 curve.

A review of aircraft environmental control system simulation and diagnostics

The aircraft Environmental Control System (ECS) enables the aircraft to maintain a comfortable and safe environment for its passengers throughout its operating envelope. The Pressurised Air Conditioner (PACK) is the heart of the ECS, and is composed of multiple sub-systems: heat exchangers, valves, compressor, turbine, and a water separator. The PACK’s principle function is to enable conditioning of the hot, high pressure bleed air from the engine or APU, for temperature, pressure and humidity against the cabin requirements. The operation of the PACK is governed by a control system which has the ability to mask degradation in its component during operation until severe degradation or failure results. The required maintenance is then both costly and disruptive. The PACK has been reported as major driver of unscheduled maintenance by the operators. The aviation industry is currently proactively exploring innovative health management solutions that aid the maintenance of aircraft key systems based on predictive based maintenance approaches using online condition monitoring techniques. This paper presents a comprehensive review of the simulation and diagnostic methodologies applicable to fault diagnostics of the ECS PACK. The existing literature suggests that model-based and data-driven methods are effective for conducting fault detection and isolation of the PACK system. The conceived findings indicate that the model-based diagnostic approach have been extensively employed to conduct PACK diagnostics at component level only. Their successful implementation requires robust experimental verification and validation against the actual data under healthy and faulty conditions. Although a substantial amount of work has been reported on developing first principles based simulation models and diagnostic strategies for the ECS, the acquired findings suggest that there is a compelling need for a verified and validated ECS simulation model to enable accurate PACK system-level diagnostics based on single and multiple component level degradation scenarios. It has also been identified that the existing literature lacks the evaluation of humidity regulation and the effect of the control system on the PACK performance characteristics. Finally, a taxonomy of diagnostic techniques and simulation models is compiled based on the available literature.

Reinforcement learned adversarial agent (ReLAA) for active fault detection and prediction in space habitats

With growing interest for human space tourism in the twenty-first century, much attention has been directed to the robust engineering of Environmental Control and Life Support Systems in space habitats. The stable, reliable operation of such a habitat is partly achieved with an ability to recognize and predict faults. For these two purposes, a reinforcement learning adversarial agent (ReLAA) is utilized in this work. A ReLAA is trained with experimental data to actively recognize and predict faults. These capabilities are achieved by proposing actions that activate known faults in a system. Instead of issuing these harmful actions to the actual hardware, a digital twin of the mock space habitat is simulated to discover vulnerabilities that would lead to faulted operation. The methods developed in this work will allow for the discovery of damaging latent behavior, and the reduction of false positive and negative fault identification.

An OCF-IoTivity enabled smart-home optimal indoor environment control system for energy and comfort optimization

The growing energy demand with diminishing energy resources calls for development of optimal indoor control system through accurate energy and occupant comfort modeling in a smart-home. While some major obstacles faced by smart-home IoT network are heterogeneity and disparate IP frameworks resulting in a connectivity and interoperability issues. In this paper we developed a new Open Connectivity Foundation (OCF) based prediction assisted optimal control framework for optimizing energy consumption and maximizing occupant comfort in smart-home. To the best of our knowledge, we are the first to design a scalable, secure, and inter-operable optimal control solution for smart-home IoT networks. The developed framework offloads machine learning models on IoT device for accurate energy and thermal comfort modeling to enable prediction assisted optimization. The system enables edge analytics using deep learning based inference models for proactive response. For optimization standard Firefly algorithm is modified based on inertia weight approach to achieve improved performance. OCF based optimal actuator control test-bed deployment and real-time experimentation is conducted to evaluate the performance of the system. Empirical investigation verified the effectiveness of proposed framework with energy saving scope of 36.82%, 5 s average response time and 3.36 MS Round Trip Time.

Development of a Nondestructive Moldy Coffee Beans Detection System Based on Electronic Nose

Coffee drinks prepared from moldy coffee beans can adversely affect human health. No convenient screening method for detecting the smell of stale coffee beans exists. Accordingly, this study developed an electronic nose (E-nose) system for detecting the smell of coffee beans. This system comprises an environmental control system, a sensor array, and a data signal readout system. The system can distinguish various degrees of mold on coffee beans through the recognition of the smell of the coffee beans. In this study, we established a standard operating procedure to collect gas samples from coffee beans in a temperature- and humidity-controlled environment and recorded changes in the signals by using the sensor array after introducing the target gas. Features were first extracted from the collected data, then dimensionality reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to these features. Thus, their complexity was reduced, and the noise was eliminated. K-nearest neighbor (KNN) and support vector machine (SVM) were adopted as classification algorithms, and the classification accuracy of the proposed system reached 91.77%.

Occupants’ Decision-Making of Their Energy Behaviours in Office Environments: A Case of New Zealand

Understanding how occupants behave and interact with building systems is vital to energy efficiency in buildings. The building occupants’ behaviours are complex and influenced by diverse factors. A deep understanding of the underlying environmental, contextual, social, and psychological factors is the first step of many in establishing the relationship between the indoor environment and occupants’ behaviours. The current study investigates the influence of occupants’ perceived indoor environmental comfort, the availability of control, and the social-psychological impacts on occupant behaviours in a New Zealand context. The data were collected through online surveys, and 99 office occupants responded. A machine learning technique was applied to identify the critical factors influencing the decision-making of occupant behaviours. Of the occupant behaviours considered in the study, adjusting windows, doors, shades and blinds, and drinking beverages were mostly practised (>70%) while adjusting lighting, personal fans, thermostats/heaters, and computers (40–70%) was moderately practised by occupants. The availability of specific user controls was the main predictor of most occupant behaviours, followed by social-psychological factors such as actual knowledge, perceived knowledge, behavioural interventions, subjective norms, organisational support, personal norms, attitudes, and perceived behavioural control. The indoor environmental parameters such as indoor temperature, indoor air quality, natural light, and inside noise were highlighted as most influential in decision-making for occupant behaviours. Additionally, the demographic factors: gender, work duration, days at work, and permanence/temporariness of workspace, were also impactful. Knowing the complexity of occupants’ decision-making with respect to their behaviours helps building managers use this sensitive information to enhance building energy performance and enable more energy feedback to the occupants to raise their awareness. Such information is helpful for creating an intelligent environmental control system loop with eco-feedback and establishing occupant-centric buildings or features.

Evaluation of Component Level Degradation in the Boeing 737-800 Air Cycle Machine

Abstract An aircraft is composed of several highly integrated and complex systems that enable it to deliver safe and comfortable flight. Its functionality is therefore strongly dependent on the safe operation of these systems within their designed optimal efficiencies. The air cycle machine (ACM) is a subsystem of the pressurized air conditioner (PACK) system, its key function is to enable refrigeration of the air in order to comply with the wide range of cabin environment requirements for maintaining aircraft safety and passenger comfort. The operation of the ACM is governed by the PACK control system which can mask degradation in its component during operation until severe degradation or failure results. The required maintenance is then both costly and disruptive. The ACM has been reported as one of the most frequently replaced subsystem and has been therefore reported as a major driver of unscheduled maintenance by the operators. This paper aims to investigate the component level degradation in the ACM at various severities and quantify the impact of its performance characteristics and associated interdependencies at PACK system level. In this paper, Cranfield University’s in-house environmental control system (ECS) simulation framework called simscape ECS simulation under all conditions (SESAC) has been implemented to evaluate degradation in the ACM components in a representative Boeing 737-800 aircraft PACK model. The fault modes of interest are those highlighted by the operators and correspond to the ACM compressor, turbine, and interconnecting mechanical shaft efficiency degradation. Simulation results, in terms of temperature, pressure, and mass flow at various degradation severities, are presented and discussed for each component at PACK system level. The acquired results suggest that, for all three fault modes, the PACK controller can compensate for an ACM degradation severity of up to 20%, allowing the PACK to sustain the delivery of the demanded temperature and mass flow. For degradation severity of above 20%, the PACK is able to deliver the demanded temperature with a substantially reduced mass flow. This has a significant impact on the PACK’s ability to meet the cabin demand efficiently. The methodology reported and the findings conceived to serve as an enabler toward formulating an effective PACK fault diagnostics and condition monitoring solution at system level, and fault reasoning at vehicle level.

Development of an Air Electric Compressor for a No-Bleed Environmental Control System of an Advanced Regional Aircraft

BACKGROUND: Aircraft designers strive to increase the fuel efficiency of aircrafts, including increasing the efficiency of aviation environmental control systems (ECS) by introducing an autonomous source of compressed air with an electric drive as part of aircraft.
 AIM: The present paper aimed to consideration of the results of research work (RD) of the technologies demonstrator for the electric compressor of the aircraft electric ECS and estimation of the performance and compliance of the simulated and experimental characteristics of this electric compressor.
 MATERIALS AND METHODS: Comparison of the simulated and experimental characteristics of the electric compressor of the electric ECS of the aircraft was carried out by confirming the compliance of the operating parameters of the technologies demonstrator for the electric compressor with those specified in the request for proposals (RFP), and by comparing the simulated and experimental values of the compression ratio of the compressor stage, isentropic coefficient of performance (COP), obtained during RD study.
 RESULTS: Information about the technical characteristics and design of the electric compressor is given and discussed. A comparative analysis of the presented simulated and experimental characteristics of the electric compressor has been carried out.
 CONCLUSIONS: Conclusions are drawn on the compliance of the compressor characteristics with the characteristics specified in the RFP; on the achieved level of readiness of the technology of the electric compressor for the electric ECS of the aircraft, on the need for experimental design work on the electric compressor, taking account of external influencing factors typical for an application as part of aviation equipment.

Acoustic monitoring of an aircraft auxiliary power unit

In this paper, the development and implementation of a novel approach for fault detection of an aircraft auxiliary power unit (APU) has been demonstrated. The developed approach aims to target the proactive identification of faults, in order to streamline the required maintenance and maximize the aircraft’s operational availability. The existing techniques rely heavily on the installation of multiple types of intrusive sensors throughout the APU and therefore present a limited potential for deployment on an actual aircraft due to space constraints, accessibility issues as well as associated development and certification requirements. To overcome these challenges, an innovative approach based on non-intrusive sensors i.e., microphones in conjunction with appropriate feature extraction, classification, and regression techniques, has been successfully demonstrated for online fault detection of an APU. The overall approach has been implemented and validated based on the experimental test data acquired from Cranfield University’s Boeing 737-400 aircraft, including the quantification of sensor location sensitivities on the efficacy of the acquired models. The findings of the overall analysis suggest that the acoustic-based models can accurately enable near real-time detection of faulty conditions i.e., Inlet Guide Vane malfunction, reduced mass flows through the Load Compressor and Bleed Valve malfunction, using only two microphones installed in the periphery of the APU. This study constitutes an enabling technology for robust, cost-effective, and efficient in-situ monitoring of an aircraft APU and potentially other associated thermal systems i.e., environmental control system, fuel system, and engines.

Toxicity of carcinogenic pahs in boiler flue gases thermal capacity up to 1 Mw

THE PURPOSE. In accordance with the new requirements of domestic environmental legislation, technological principles of state regulation of the negative impact of energy enterprises on the environment have been introduced. The established principles of environmental protection activities provide for technological regulation of emissions based on the introduction of the best available technologies, as well as differentiation of state regulatory measures to ensure the environmental safety of thermal power facilities. Within the framework of the current environmental legislation, it is shown that it is necessary to determine emission standards for highly toxic substances that have carcinogenic properties. The main representatives of carcinogenic PAHs found in the flue gases of boilers of low power up to 1 MW are considered.METHODS. The research methods included the generalization of experimental data and thecalculated assessment of the content of carcinogenic emissions, including benz(a)pyrene in the flue gases of boilers using statistical data processing methods.RESULTS. The necessity of taking into account the contribution of the harmfulness of carcinogenic PAHs in the system of industrial environmental control at thermal power facilities during the operation of low-power boilers is determined.CONCLUSION. The results of the study can be used at energy enterprises to implement the requirements of the new environmental legislation in terms of technological regulation of carcinogenic emissions, including for the development of measures to improve environmental performance indicators.

The impact of assistive living technology on perceived independence of people with a physical disability in executing daily activities: a systematic literature review

Purpose People with physical disabilities often require lifetime support and experience challenges to maintain or (re)define their level of independence. Assistive living technologies (ALT) are promising to increase independent living and execution of activities of daily living (ADL). This paper provides a systematic literature review that aims to analyse the present state of the literature about the impact of ALT on perceived independence of people with a physical disability receiving long-term care. Materials and methods Databases Embase, Medline, and Web of Science were searched for eligible studies from 2010 or later. Results Nine studies were included, of which seven qualitative, one quantitative, and one mixed methods. Quality was generally high. ALT enabled participants to execute ADL. We found six themes for the impact of ALT on perceived independence: feeling enabled, choice and control, feeling secure, time alone, feeling less needy, and participation. Conclusions ALT appears to impact perceived independence in many ways, exceeding merely the executional aspect of independence. Existing research is limited and quite one-sided. More large-scale studies are needed in order to inform care organisations how to implement ALT, especially considering societal developments and challenges impacting long-term care.

Internet of Things (IoT)-Based Environmental Monitoring and Control System for Home-Based Mushroom Cultivation

The control and monitoring of the environmental conditions in mushroom cultivation has been a challenge in the mushroom industry. Currently, research has been conducted to implement successful remote environmental monitoring, or, in some cases, remote environmental control, yet there is not yet a combination of both these systems providing live stream images or video. As a result, this research aimed to design and develop an Internet of things (IoT)-based environmental control and monitoring system for mushroom cultivation, whereby the growth conditions of the mushrooms, such as temperature, humidity, light intensity, and soil moisture level, are remotely monitored and controlled through a mobile and web application. Users would be able to visualize the growth of the mushroom remotely by video and images through the Internet. The respective sensors are implemented into the mushroom cultivation process and connected to the NodeMCU microcontroller, which collects and transfers the data to the cloud server, enabling remote access at any time through the end device with internet connection. The control algorithm regulates the equipment within the cultivational chamber autonomously, based on feedback from the sensors, in order to retain the optimum environment for the cultivation of mushrooms. The sensors were tested and compared with manual readings to ensure their accuracy. The implementation of IoT toward mushroom cultivation would greatly contribute to the advancement of the current mushroom industry which still applies the traditional cultivation approach.

Exploring the Impact of Kinetic Façade Environmental Control Systems in the Development of Sustainable Design: A Systematic Literature Review

In this study, a systematic literature review (SLR) was conducted primarily aimed to assess the existing literature pertaining to the utilisation of kinetic façade environmental control systems (ECS) in developing building designs that are highly sustainable. For this purpose, the search strategy was initiated by using various databases including Google Scholar, ProQuest, EBSCOhost, SCOPUS and Springer, etc. The inclusion criteria for the studies were based upon the investigation of the use of kinetic façade ECS in sustainable design. Moreover, the timeframe for the inclusion of the papers was kept between 2012 and 2021. Using these inclusion criteria, the search was conducted and a sample of 13 papers was selected from different databases. The data were extracted from these papers and were subjected to analysis. The findings of the SLR explicitly showed that different façade systems are highly energy efficient because of the innovative techniques used in their construction. In the building design process, the development of kinetic facades is given due attention for the purpose of maintaining comfortable internal conditions as compared to the outside environment. As technology and smart systems improve, the involvement of façades in developing energy-efficient and more comfortable design methodologies will gain more attention. Moreover, the findings of SLR depicted that the kinetic facades are quite important in terms of attaining desired daylighting within the buildings. Also, SLR found that studies particularly focus on the use and integration of technology when designing kinetic facades which should consider the ecological context into consideration during the development of such building architectures.

An Aisle Displacement Ventilation System for Twin-Aisle Commercial Airliner Cabin

The environmental control system in most commercial airliner cabins supplies air from shoulder and ceiling level and exhausts air at floor level on both sides of the cabin walls. The ventilation system mixes air in the cabins to create a relative uniform air temperature distribution which is great for passengers’ thermal comfort. However, the mixing ventilation also enhances airborne contaminant transfer. Many displacement ventilation methods have been proposed to use in aircraft cabins, but the disadvantages of the ventilation approach are usually creating draft on the passengers’ ankles and high air temperature stratification between passengers’ heads and feet. This investigation developed an aisle displacement ventilation (ADV) system which can reduce air temperature stratification effectively without occupying the legroom space under the seats, so it is good for passengers and crew members’ comfort and friendly for luggage storage, in addition, it can also be easily installed in aircraft cabins. By installing the system in a five-row, twin-aisle cabin mockup, our study found that the ADV system can create a low air velocity distribution in the cabin and can maintain an acceptable air temperature stratification without draft. The system created an uprising airflow which can effectively remove airborne contaminant which was generated from index passengers’ respiratory activities. The experimental data were used to validate a computational-fluid-dynamics (CFD) program. The validated CFD program was used to compare the ADV with under-seat displacement ventilation (USDV) and underfloor air distribution (UFAD) system along the aisles. The comparison results show that the ADV had obvious better thermal comfort than the other two systems, and the cabin air quality of the three ventilation systems was similar, all far better than the “perfectly-mixed” ventilated condition.

Stochastic MPC Based Attacks on Object Tracking in Autonomous Driving Systems

Decision making in advanced driver assistance systems involves in general the estimated trajectories of the surrounding objects. Multiple object tracking refers to the process of estimating in real time these trajectories, leveraging for this purpose sensors to detect the objects. This paper deals with devising attacks on object tracking in automated vehicles. The vehicle is assumed to have a detection-based object tracking system that relies on multiple sensors and uses an estimator such as a Kalman filter for sensor fusion and state estimation. The attack goal is to modify the object's state estimated by the victim vehicle to put the vehicle in an unsafe situation. This goal is achieved by judiciously perturbing some or all of the sensor outputs corresponding to the object of interest over a desired horizon. A stochastic model predictive control (SMPC) problem is formulated to compute the sequence of perturbations, whereby hard constraints on the perturbations and probabilistic chance constraints on the object's state are imposed. The chance constraints ensure that some desired conditions for a successful attack are satisfied with a prespecified probability. Reasonable assumptions are then made to obtain a computationally tractable linear SMPC program. The approach is demonstrated on an adaptive cruise control system in a simulation environment, where successful sequential attacks are generated, leading the victim vehicle into dangerous driving situations including collisions.

On-orbit Space Technology Experiment and Verification Project Outlook of China’s Tiangong Space Station

China’s Tiangong space station has been completed in 2022 to support large-scale multidisciplinary space science research and technology experiments. With a large payload capacity and long operating time, Tiangong space station has many irreplaceable advantages over other spacecraft, such as space transportation, global tracking, on-orbit care for astronauts, and the ability to replace and upgrade experiment equipment. The resources available to the space station and its affiliated spacecraft provide an excellent open verification platform for experimental programs. The modular design of the intravehicular experiment rack can support different combinations of normal payloads for experiment, and an extravehicular exposed platform is planned to support different sizes of normal payloads for experiment. This paper firstly discusses the mission objectives of China’s Tiangong space station and the development of new space systems. Secondly, it sorts out the conditions for China’s Tiangong space station to conduct experiments for space technology. On this basis, a systematic layout for the missions of space technology experiments on China’s Tiangong space station is made. Five research topics are proposed, i.e., robotics and autonomous system technology, on-orbit assembly and construction technology for spacecraft, environmental control and life support system technology, new energy and propulsion technology, and new generic technology for spacecraft. Centering on the key technologies that restrict the development of China’s future space missions and systems, this study gives an outlook on the on-orbit space technology experiment and verification project for China’s Tiangong space station. Finally, development strategy and suggestions are put forward for China’s space technology.

GREENBOX Technology III - Financial Feasibility for Crop Production in Urban Settings

Highlights We proposed to use GREENBOX technology for urban crop production in warehouse settings. We assessed the profitability of the application of GREENBOX technology using Benefit Cost Analysis (BCA) to evaluate the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). We conducted sensitivity analyses on NPV, IRR, and PP over different scenarios. GREENBOX was found financially feasible for all the hypothetical scenarios in major cities in the USA. Abstract. Food security pressure, especially in urban areas, continues to rise due to surging demand for food resulting from a growing population and declining resources. It has been critical to improve crop production and make food readily available to consumers without traveling long distances in an economically sustainable manner. The novel GREENBOX technology uses Controlled Environment Agriculture (CEA) principles for leafy green crop production in urban structures. A GREENBOX is an individual thermally insulated chamber with an artificial lighting source and a soilless cultivation system (hydroponics) in an environment that is controlled at the grower's discretion. This study performed a financial feasibility study of GREENBOX technology for urban crop production in various scenarios to evaluate the system's profitability from an individual business's perspective and used market prices of the goods and services paid for or received by a project. The representative GREENBOX unit in the base case scenario had dimensions of a standard shipping pallet (1.0 x 1.2 x 0.9 m, or 40 x 48 x 36 in) and included thermally insulated walls, an LED artificial lighting source, a camera for monitoring growth, a Nutrient Film Technique (NFT) hydroponic growth platform, and an environmental monitoring and control system. A warehouse can host numerous GREENBOX units for mass production. We carried out a benefit-cost analysis by assessing the Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). These parameters were evaluated for a base case scenario from data collected or estimated for a representative GREENBOX unit. We also applied the base case scenario to investigate the financial performance of the GREENBOX setup in selected urban areas in the United States; New York City (New York), Miami (Florida), Los Angeles (California), Dallas (Texas), Atlanta (Georgia), Chicago (Illinois), Boston (Massachusetts), and Philadelphia (Pennsylvania). We then carried out a sensitivity analysis on NPV, IRR, and PP by keeping all the parameters in the base case scenario invariant except for one at a time. We obtained a summary equation to understand the variation of the financial parameters with changing lettuce sale price, electricity cost, rental cost, labor cost, and the number of GREENBOX units. A GREENBOX unit would require an initial investment of $398 to assemble and an annual outflow of $157 to cover operating expenses. GREENBOX cultivation was financially viable in the base case scenario and in all the cities studied, with varying degrees of financial performance. The sensitivity analysis revealed that GREENBOX cultivation was financially viable in all scenarios except when skilled labor costs were beyond $19/hr, and there were fewer than 300 GREENBOX units. A statistically significant regression equation was derived in which rising rental costs, labor costs, and electricity prices negatively impacted the NPV, while the rising lettuce sales price and the number of GREENBOX units positively impacted the NPV. GREENBOX farming may serve as a local source of fresh crops for urban customers, with various benefits including improved food security, greater freshness and nutrition of food, the potential to contribute to the local economy by the creation of jobs and revenues from sales, and educational opportunities through extension programs on food nutrition and production. Keywords: Agricultural business, Environmental control, GREENBOX, Lettuce, Urban agriculture.

Smart control system for the precision cultivation of black fungus

Black fungus, with high nutritional and medicinal value, has been cultivated in China for a long time, and Heilongjiang alone accounts for about 40% of the global output. At present, the cultivation of black fungus derives mainly from the inheritance of relatively primitive practices and experience of farmers, resulting in inconsistent quality of fungus. In this study, a smart control system for the precision cultivation of black fungus was designed by using intelligent detection and control technology. The system includes a precision culture test environment and remote control system. The precision cultivation environment contains four sub-independent environments. The key parameters such as temperature, humidity, and light behavior were collected and can be adjusted individually, according to the precision cultivation stages. The intelligent remote control system included a controller cabinet, sensors unit, temperature control unit, humidity control unit, light control unit, and information transmitting unit. The controller cabinet includes a key controller which can auto-control the temperature, humidity, and lightly adjust components according to the precision cultivation conditions and processing. The temperature sensors were installed in a 3D array close to the fungus bags about 5 cm in rooms. The light tape was installed on the six walls and also had three colors (Red, Blue, and Green) which could be controlled independently in each room. The control strategy through the analysis of the data collected by all sensors, the current cultivate situation of the cultivation environment was obtained, and the heater, fan, light, and nozzle were regulated according to the strategy to maintain a suitable precision cultivation environment for fungus. To verify the feasibility of the precision cultivation processing and control system, the test result shows that the error of temperature control was about 0°C-1°C, the error of humidity control was about 1%-4%, and the error of illuminance control was about 0-50 lx; All the verification results show that the control system for precision cultivation has high precision and can meet the needs of exploring the "Black 29" fungus cultivation experiment environment. Based on the orthogonal experiment, the best combination of the temperature and humidity for each growth stage was also investigated in this study, further proving the reliability and feasibility of the control system for the precision cultivation of Auricularia auricula. Keywords: black fungus, precision cultivation, smart control system, growth environment, remote control system, sensor DOI: 10.25165/j.ijabe.20231601.6257 Citation: Jiang Y C, Li J J, Li Y, Li S D, Song X, Wu H Y, et al. Smart control system for the precision cultivation of black fungus. Int J Agric & Biol Eng, 2023; 16(1): 193–202.

Causal Signal Temporal Logic for the Environmental Control and Life Support System’s Fault Analysis and Explanation

Modern cyber-physical systems would often fall victim to unanticipated anomalies. Humans are still required in many operations to troubleshoot and respond to such anomalies, such those in future deep space habitats. To maximize the effectiveness and efficiency of the anomaly response process, the information provided by anomaly response technologies to their human operators must be epistemically accessible or explainable. This paper offers a first step towards developing explainable anomaly response systems. It proposes a logic, Causal Signal Temporal Logic (CaSTL), which can formally describe cause-effect relationships pertaining to fault explanation. Moreover, it develops an algorithm to infer a CaSTL formula that explains why a fault has happened in a system, given the model of the system and an observation about the fault. The effectiveness of the proposed algorithm is demonstrated with a simulated Environmental Control and Life Support System (ECLSS).