AIMC Topic: Hydrocarbons

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Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning.

Environmental toxicology and chemistry
Technical complexity associated with biodegradation testing, particularly for substances of unknown or variable composition, complex reaction products, or biological materials (UVCB), necessitates the advancement of non-testing methods such as quanti...

Physics-guided neural network for predicting asphalt mixture rutting with balanced accuracy, stability and rationality.

Neural networks : the official journal of the International Neural Network Society
The prediction of rutting performance of asphalt materials poses a significant challenge due to the intricate relationships between the rutting performance and its influencing factors. Machine learning models have gained popularity to address this ch...

Saline wastewater treatment by bioelectrochemical process (BEC) based on Al-electrocoagulation and halophilic bacteria: optimization using ANN with new approach.

Environmental technology
In the present study, a bioelectrochemical reactor (BEC) was utilized to treat two types of real saline produced water (PW). BEC was designed based on the combination of electrocoagulation (EC) process with halophilic microorganisms, and it was asses...

Intelligent Diagnosis Based on Double-Optimized Artificial Hydrocarbon Networks for Mechanical Faults of In-Wheel Motor.

Sensors (Basel, Switzerland)
To avoid the potential safety hazards of electric vehicles caused by the mechanical fault deterioration of the in-wheel motor (IWM), this paper proposes an intelligent diagnosis based on double-optimized artificial hydrocarbon networks (AHNs) to iden...

Research on water seepage detection technology of tunnel asphalt pavement based on deep learning and digital image processing.

Scientific reports
To improve the safety of road tunnel pavement, the research established road tunnel pavement water seepage recognition models based on deep learning technology, and a water seepage area extraction model based on image processing technology to finally...

A Connectionist Model for Dynamic Economic Risk Analysis of Hydrocarbons Production Systems.

Risk analysis : an official publication of the Society for Risk Analysis
This study presents a connectionist model for dynamic economic risk evaluation of reservoir production systems. The proposed dynamic economic risk modeling strategy combines evidence-based outcomes from a Bayesian network (BN) model with the dynamic ...

Data-driven method based on deep learning algorithm for detecting fat, oil, and grease (FOG) of sewer networks in urban commercial areas.

Water research
The content of fat, oil and grease (FOG) in the sewer network sediments is the key indicator for diagnosing sewer blockage and overflow. However, the traditional FOG detection is time-consuming and costly, and the establishment of mathematical models...

Adaboost Algorithm in Artificial Intelligence for Optimizing the IRI Prediction Accuracy of Asphalt Concrete Pavement.

Sensors (Basel, Switzerland)
The international roughness index (IRI) for roads is a crucial pavement design criterion in the Mechanistic-Empirical Pavement Design Guide (MEPDG). However, studies have shown that the IRI transfer function in the MEPDG is simply a linear combinatio...

Deep-learning based monitoring of FOG layer dynamics in wastewater pumping stations.

Water research
Accumulation of fat, oil and grease (FOG) in the sumps of wastewater pumping stations is a common failure cause for these facilities. Floating solids are often not transported by the pump suction inlets and the individual solids can accumulate to sti...

Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils.

Ecotoxicology and environmental safety
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...