bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbonaceous materials derived from biowastes pyrolysis as efficient and green biogas desulfurization system
Authors: Marone M , Marasco P , Trotta S , Carnevale A , Salvatori M , Fedele M , Contillo F , Francavilla M
Published: December 2023

The desulfurization performance of carbonaceous material achieved by slow pyrolysis of different kinds of organic raw biomass has been investigated to provide a greener alternative to using activated carbons and contribute to using available resources more efficiently and sustainably. Nine different raw feedstocks and biowastes were used as biomass precursors for biochar production at different pyrolysis conditions. In particular, six of them originated from lignocellulosic biomass (olive pruning, woods pruning, olive stone, spent coffee grounds, solid digestate from cattle, solid digestate from a mix of cattle and pigs), while the other three were from aquatic biomass (crabs’ blue shells, mussels’ blue shells, and microalga Chlorella sorokiniana). The H2S adsorption performances of the different biochar samples were then evaluated compared to commercial activated carbons, the technology currently in use. Moreover, the chemical composition of biochar (before and after H2S adsorption) was investigated to understand better the physical-chemical mechanism that regulated the adsorption. The results showed significant differences in the H2S adsorption capacity of biochars according to their origin (raw biomass) and operating conditions of pyrolysis (temperature and residence time), with the best performance achieved by biochar from olive pruning and microalga Chlorella. Interestingly, a combined mechanism of physio adsorption and chemical oxidation of H2S to elemental Sulphur (S) and sulphate (SO4
2-) was found.
Power-to-liquid versus biomass-derived kerosene: a comparative study
Authors: Manente Giovanni , Ficarella Antonio , Rahim Ahtasham
Published: December 2023

Power-to-Liquid (PtL) kerosene is considered by many experts as the only viable option to achieve a large scale decarbonization of the aviation sector in the near-medium term. In the PtL process carbon dioxide of renewable origin or from ambient air and green hydrogen are combined to produce a liquid fuel that can replace fossil kerosene. For this purpose the Fischer-Tropsch pathway and the methanol pathway are available. On the other hand, more production pathways are available when using a biomass feedstock. The aim of this work is to compare the power and biogenic routes for the production of sustainable kerosene in terms of performance and requirements. Indeed, there is a lack of studies in the literature that directly compare the two options, i.e. biofuels and e-fuels, on a common basis. Accordingly, simulation models are built in this work for both routes to calculate the yield of kerosene and co-products, the hydrogen demand, the flows of carbon dioxide, the electricity and thermal energy demands. The simulation outputs are compared against the results of the relevant studies in the literature. The expectation from this comparative study is to highlight the criticalities of each route and, possibly, any opportunity to overcome them by exploring any synergy between the different routes.
Analysis of combined cycle plants integrating biomass and natural gas
Authors: Morrone Pietropaolo , Falbo Luigi , Settino Jessica , Fragiacomo Petronilla , Ferraro Vittorio , Arcuri Natale
Published: December 2023

Biomass plays a vital role in broadening the energy portfolio and reducing reliance on traditional fossil fuels. Combining biomass with natural gas-powered combined cycle plants offers an opportunity to improve biomass conversion efficiency. This study aims to conduct a comprehensive technical and economic analysis, comparing two configurations of combined-cycle plants fueled by natural gas and lignocellulosic biomass. The first configuration implements traditional post-combustion methods to augment steam cycle output, while the second directs exhaust gases to a heat exchanger, pre-heating the compressor’s outgoing air. A significant focus was placed on assessing biomass conversion efficiency, specifically the marginal efficiency in electricity generation attributed to biomass input. This parameter was compared with the performance of standard conventional biomass-only plants. The research delved into the impact of varying biomass feed ratio on key performance indicators, including the cost of electricity generation, the overall and marginal biomass efficiency, and the share of electricity production due to biomass. The determination of the optimal plant configuration and the ideal biomass fraction was achieved through multivariable optimization techniques.
Monitoring and analysis of environmental and IAQ conditions in classrooms with controlled mechanical ventilation
Authors: Remia G. , Summa S. , Stazi F. , Di Perna C.
Published: December 2023

Following the health emergency from COVID-19, indoor air quality control has become of paramount importance, especially inside school buildings. For this reason, in 2021, the Marche region proposed and implemented an extraordinary intervention for the safe conduct of educational activities through the installation in classrooms of controlled mechanical ventilation systems aimed at air exchange. This type of system has been installed in more than 1,200 classrooms belonging to about 130 schools throughout the Marche region. This intervention made it possible to carry out a robust experimental measurement campaign on a significant number of classrooms where controlled mechanical ventilation systems were installed. Specifically, the work proposes a replicable measurement and analysis methodology for classrooms, with the aim of monitoring thermo-hygrometric and air quality conditions for environmental comfort. Thus, the research aims to implement knowledge on environmental comfort in classrooms equipped with controlled mechanical ventilation systems. The proposed measurements and analyses cover the most important environmental variables, i.e., air temperature, relative humidity, and CO2 concentration. In addition, measurements regarding system ventilation flow rates, smoke tests and evaluations of the permeability of classrooms.
A statistical analysis of exhaled respiratory droplet trajectory distribution in view of assessing the risk of infectious disease transmission
Authors: Cavazzuti M , Campanelli L , Tartarini P
Published: December 2023

In the present work an analytical model of exhaled droplet trajectory and evaporation is employed to perform a preliminary statistical analysis of the droplet spatial distribution. The analysis is carried out for a set of over twenty thousand droplets distributed in the range of diameters from 0.1 μm to 1 mm. The type of respiratory events modelled are mouth breathing and speaking. The analytical model employed has been recently developed by the authors. It implements the fundamental laws of fluid dynamics and convection-diffusion, and features a 2D empirical numerical model of buoyant intermittent jet modelling the exhaled breath cloud. A discrete random walk turbulent dispersion model is also included allowing statistical analysis of the droplet trajectory to be performed. With proper boundary conditions any type of respiratory event can be simulated making the model particularly versatile. From the analysis, spatial virus concentration maps are derived for the largest droplets falling to the ground, and for the smaller droplets remaining airborne in the area in front of an infected emitter and successively uniformly dispersed in the ambient. This allows to estimate the risk of infection by fomite, direct inhalation and indirect inhalation routes, and provide a better understanding of infectious disease transmission risks.
Building a Renewable Energy Community for the Tor Sapienza district in Rome
Authors: Romano G , Margani P , Mancini F , Battisti A
Published: December 2023

The transition away from fossil fuels towards a carbon-neutral, clean and circular economy is one of the greatest challenges of our time. Energy communities are one of the tools to re-structure our energy systems by harnessing the energy and allowing citizens to participate actively in the energy transition and thereby enjoy greater benefits.

The definition of Renewable Energy Communities (RECs) given by the European Commission, places the REC as an association that produces and shares renewable energy, generating and managing cost-effective green energy autonomously, reducing CO2 emissions and energy waste. Observing this definition, the new Italian regulations concerning RECs boost distributed generation, encouraging the development of ‘zero-mile’ local energy production and smart grids. This research aims to evaluate the conditions to propose a REC in the Tor Sapienza district, as an Italian prototype, assessing the possibilities and advantages of transforming it into a large-scale sustainable infrastructure by means of a deep energy transition and the active role of local citizens, public administrations and small and medium-sized enterprises. Thanks to an in-depth technological, environmental and demographic survey of the neighbourhood, the study focuses on the retrofitting of a social housing complex in Tor Sapienza, as the main prosumer of the REC.
Analysis of the electrical and thermal behaviour of Li-ion batteries using 0D and 3D-CFD approaches with validation on experimental data
Authors: Reina L , Grigore C , Cicalese G , Fontanesi S
Published: December 2023

Due to their characteristics, lithium-ion cells are the reference in the construction of a battery pack for electric vehicles (EVs). Despite this, their use is strongly affected by the operating temperature because the materials they are made of are thermally stable only in a relatively limited range around ambient temperature. Cell modelling and simulation become therefore essential in the design of the cell, of the battery pack and of its auxiliary systems to optimize performance while maintaining sufficient safety margins.

In the present study, two zero-dimensional equivalent circuit models of a commercial Li-ion cell are developed and tuned in order to predict the electrical and thermal behaviour of the cell. The models are validated and compared with experimental data found in the scientific literature referring to both dynamic and static tests. This comparison shows the importance of tuning the model parameters, which are decisive for the accuracy of the simulation.

Using a commercial tool dedicated to battery modelling, a three-dimensional model is then developed to investigate the electrical and thermal behaviour of the cell from a spatial point of view. The results obtained are aligned with those found in the scientific literature.

With the present work, it has been possible to simulate and analyse the global behaviour of the cell (0D model) as well as its detailed behaviour (3D model) using relatively modest computational resources, thus constituting a solid base for more complex modelling such as that of a battery pack and its cooling system.
Tribological investigation of friction coefficient in pneumatic seals with a special pin-on-disc setup
Authors: Mazza Luigi , Trivella Andrea , Goti Edoardo
Published: December 2023

This article presents an experimental method for measuring friction in seals for pneumatic actuators using a pin-on-disk tribometer in a linear reciprocating sliding motion. A special device was designed to test a segment of seal cut out of a seal ring to replicate the working conditions of the piston seals. Friction tests were carried out with spring-energised seals made of graphite-filled PTFE. The counterpart for the friction test was a portion of an actual cylinder barrel of a pneumatic actuator. The coefficient of friction was measured under different loads to replicate several mounting preloads. Moreover, the experimental results were compared to the friction coefficient measured with a flat pin of the same seal material against a flat counterpart. The comparison between the two test setups allowed the authors to study the effect of the contact geometry and the applied load on the tribological performance of the seal. These preliminary measurements of stiffness and coefficient of friction are the basis for further investigations and measurements of elastic, viscoelastic and friction properties at the lip-barrel contact to develop a wear-damage model of lip seals.
Techno-economic analysis of hydrogen production via photovoltaic, battery and electrolysis: plant sizing and hydrogen cost.
Authors: Tamburrano G. , Zotto L. Del , Zuccari F. , Caponi R. , Santiangeli A. , Di Matteo U , Orecchini F. , Bocci E.
Published: December 2023

Photovoltaic reached more than 20% panel efficiency and less than 20% system efficiency losses and 1 M€/MW cost. Similar cost is reached by electrolyzer meanwhile the efficiency can be more than 60% from 3% to 110% of the nominal power. Battery cost reached less than 0.5 M€/MWh meanwhile efficiency is higher and lifetime has reached more than 20.000 cycle if uses are within 20-80% of the state of charge. With these values the battery can be downsized (owing to the large % of electrolyzer nominal power) but still hydrogen production cost from photovoltaic is not competitive. These paper analyses what can be the better size among photovoltaic, battery and electrolyzer in order to reach the lowest hydrogen production cost with a sensitivity analysis on representative parameters (efficiencies, CAPEX and OPEX) for these technologies.
Non linear model predictive control strategy for the energy management of a P4 parallel hybrid electric vehicle
Authors: Teodosio Luigi , Bellis Vincenzo De , Landolfi Enrico , Marino Matteo , Giordano Giuseppe , Malfi Enrica , Piras Marco
Published: December 2023

In this paper, the energy management strategies (EMS) as main fuel saving approaches are studied for a P4 parallel hybrid electric vehicle (HEV). The multiple power sources of the analysed HEV (one thermal engine and two electric motors) and the different vehicle driving conditions increase the complexity in designing an optimal EMS. To efficiently solve the fuel minimization problem, a non linear Model Predictive Control (NL-MPC) is proposed as energy optimization strategy of the examined HEV. First, a vehicle simulation model is developed in Matlab/Simulink environment. A NL-MPC-controller is designed, implemented into the adopted code and coupled to the vehicle model. The effectiveness of developed NL-MPC approach is evaluated in two different driving cycles, also including various initial battery State of Charge. A comparison with a well-recognized real-time EMS strategy, namely heuristic/rule based (RB) approach, is performed over WLTC and a Real Driving Cycle (RDC). The numerical outcomes demonstrate the capability of NL-MPC controller at significantly improving the fuel consumption with respect to the RB strategy (maximum advantage of 9% and 15% over WLTC and RDC), thus providing an excellent and robust method in the HEV powertrain control with satisfactory performance.
Turbocompound energy recovery option on a turbocharged diesel engine
Authors: Battista Davide Di , Bartolomeo Marco Di , Prospero Federico Di , Diomede Domenico Di , Carapellucci Roberto , Cipollone Roberto
Published: December 2023

The transportation sector is living a transition era in which hybrid and electrified vehicles are replacing conventional vehicles, based on internal combustion engines. This is pushed by the recognized need for reducing fuel consumption and tailpipe emissions, considering primary pollutants and carbon dioxide as a greenhouse gas. In the transition path, hybridization and partial electrification of the powertrain play a crucial role. In this regard, the need for on-board electrical energy storage and utilization is increasing significantly and the possibility to recover wasted energy and convert it into electrical form is mandatory. This is especially true for commercial and heavy-duty vehicles, where full electrification is more difficult to be implemented. Waste Heat Recovery (WHR) has therefore become so important for vehicles, not only to directly reduce fuel consumption and related emissions but also to improve the feasibility of a generation of vehicles with a higher degree of hybridization that considers, for example, the electrification of auxiliaries following the so-called auxiliaries-on-demand management. Wasted heat refers mainly to exhaust heat from gases, where about one third of the fuel energy is disposed of. Among the various systems for WHR, engine turbo-compounding is approaching a mature technology. This technological option makes use of an additional turbine on the exhaust line of the engine, downstream of the turbocharging one, which converts the residual gas enthalpy into mechanical form. In this paper, the F1C Iveco 3.0 L turbocharged diesel engine is considered for verifying the performances of a turbo-compounding system. The engine was mounted on a dynamic engine test bench. In particular, the interactions with the original engine produced on the exhaust line were studied. Backpressure effects on the engine introduced by turbo-compounding were evaluated reversed in terms of extra fuel consumption. Moreover, the new equilibrium of the turbocharger was assessed and the related modifications to the engine were measured considering that the turbocharger has a control strategy based on the so-called Variable Geometry Turbine (VGT), via the modification of the Inlet Guide Vanes (IGV). The presence of a secondary turbine for WHR opens to a wider possibility of actuating the IGV and, so, the possibility to optimize the recovery considering the integrated system and all its degrees of freedom.
Hybrid-electric power unit for an ultralight aircraft
Authors: Pisapia A. M. , Volza A. , Savioli T. , Martini P. , Mattarelli E.
Published: December 2023

High power-weight ratio, reliability and efficiency are the main design goals for the propulsion system of ultralight aircraft (mass up to 650 kg). For power outputs beyond 40 kW, 4-stroke multi-cylinder SI engines are the most widespread solution, while pure electric powertrains do not appear at the moment as a practical proposition. Four stroke diesel engines would also be very attractive, in particular for military applications, but their weight is significantly higher than their gasoline powered counterpart. The goal of the study presented in this article is to develop a hybrid-electric power unit for ultralights, running on heavy fuels (diesel, kerosene, jet fuels). Reference is made to Falco EVO, by Leonardo, originally equipped by the Rotax 912 ULS/S engine (peak power 73.5 kW, weight about 60 kg): the proposed power unit has the same cylinders layout, smaller overall dimensions and almost equivalent weight. The thermal engine is an innovative two-stroke unit, coupled in parallel to a permanent magnet electric motor. The design and optimization of the hybrid power unit has been supported by CAE tools, including CAD and CFD simulations.

The results of the study show that the new hybrid system can save about 30% of fuel mass at the typical cruise conditions, and it can increase the peak power output up to 20%, compared to the reference Rotax engine. The reduction of fuel consumption can be translated into an equivalent increment of the operative range of the aircraft, or into an increase of payload (+30%, considering the Falco EVO aircraft). Finally, compared to the Rotax engine, the hybrid power unit exhibits significantly lower CO2 emissions (from -12% to -37%), thanks to the improvement of fuel efficiency.
Evaluation of the efficiency of a hybrid ICE vehicle fuelled with hydrogen compared with a fuel cell vehicle, based on a simulation model
Authors: Aliberti Dario , Ortenzi Fernando , Battaglia Vincenzo La , Marini Stefano , Vellucci Francesco
Published: December 2023

With the renewed interested in the application of hydrogen on transportation, promoted also by the EU policies, the natural technology to adopt such energy vector is the fuel cell. The aim of this paper is to compare the performances, in terms of efficiency, hybrid internal combustion engine vehicles fuelled with hydrogen and fuel cell vehicles. The potential advantages, in using the ICEs, in a parallel hybrid powertrain, even if its efficiency is lower than fuel cell one, are the more efficient transmission efficiency, due to the fact that the engine is directly connected to the wheel through a gearbox, that has traditionally a very high efficiency, while the storage system help the engine when its efficiency is very low, recovering also energy during regenerative brakes. A fuel cell vehicle is generally a series hybrid vehicle, where the fuel cell has a higher efficiency than ICE, but the energy conversion from fuel cell to the electric motor has a lower efficiency. The expected result of this comparison is that the ICE hydrogen fuelled is able to recover the great part of the efficiency Gap with a higher powertrain efficiency. The study has been made using an in-house simulation code written in ENEA, using as input data the characteristic of two different vehicles, with, their electric subsystems (battery storage, electric motors, converters etc) control strategies running fixed driving cycles (e.g. the WLTC driving cycle) and comparing the fuel consumption end the efficiency.
Development of diagnostic instrumentations for fuel cells based on consumer electronics
Authors: Dalberto Thomas , Battistella Francesco , Colbertaldo Paolo
Published: December 2023

The decarbonization process is pushing the energy sector into a transition towards clean energy vectors. In the hard-to-abate sectors, such as heavy-duty transport and industry, hydrogen can act as an energy carrier and a sector coupler. Key devices for hydrogen exploitation are fuel cells. Diagnostic is a crucial element for safety and efficiency during operation. This work regards the development process – from the conception to the validation and use – of an acquisition system made of consumer electronic components. By measuring differential voltage at high frequency, it enables to perform Electrochemical Impedance Spectroscopy (EIS). The system consists of an Arduino board running a self-developed circuit composed of an operational amplifier, an analog-to-digital converter, and a buffer memory. The system is designed to be expanded with multiple synchronized modules to monitor several cells at once. The module can be applied to a single cell or a group of cells (e.g., a stack) by tuning the operational amplifier. A dedicated software has also been developed, involving assembly language to achieve the required speed performance. The circuit has been validated using a function generator to apply sinusoids with frequencies between 100 Hz and 10 kHz and amplitudes of 10-500 mV (reflecting the EIS requirements on a single cell). An oscilloscope is used to double-check the generated signal. The results proved that the system features errors below 3% on amplitude and below 0.3% on frequency. Finally, the developed system has been tested against a commercial device performing EIS measurements. The obtained impedance values generally differ by less than 3% in the range of interest, while a few specific frequencies are affected by external disturbances.
Thermo-economic optimization of a 100 kW air-to-water heat pump for heating purposes in residential units
Authors: Viscardi I , Viscito L , Ferraro L Del , Mauro A W
Published: December 2023

In order to reach the ambitious objectives of carbon neutrality by 2050 and the limitation of the ambient temperature rise at 1.5 °C, several intensive energy fields such as heating and cooling appliances should be decarbonized. On this regard, electric heat pumps represent the most promising solutions to replace old and inefficient conventional boilers and comply with the ecological transition through the increase of electric energy production by means of renewable sources. In this paper, a thermo-economic optimization analysis of a 100 kW air-to-water electric heat pump is proposed. The appliance is designed to produce hot water at 55 °C. The developed model employs phenomenological equations calibrated on real data and manufacturer datasheets for compressor, heat exchangers, and costs. Different design options, including the heat exchangers size and the choice of the working fluid (among R32, propane R290, ammonia R717, R454C), are presented and discussed. The Pareto analysis is then employed to find the best possible configurations in terms of costs and performance.
DOE optimization of a liquid cold plate used in a thermal management system for power converters in the railway sector through 3D CFD analysis
Authors: De Rosa R , Romagnuolo L , Frosina E , Senatore A
Published: December 2023

The thermal management system for power electronics is becoming a key factor in order to guarantee optimal working conditions, efficiency and safety of those components. In the field of liquid-cooled power electronics, the design of an optimal liquid cold plate (LCP) is fundamental to increase the heat transfer, minimizing the maximum temperature and the pressure drop. This work presents an optimization procedure of a finned extruded profile of an LCP for insulated gate bipolar transistor (IGBT) power module, for railway propulsion. The optimization has been performed through DOE, by considering different values of several control factors (shape of the fin, length of the fin, pitch between the channels created by the fins), in order to minimize the LCP maximum temperature and the pressure drop between inlet and outlet. The combination of different values of control factors results in 18 prototypes, which have been compared using three-dimensional CFD simulations, performed in Ansys Fluent environment. The influence of parameters variation on the objective functions (i.e. maximum temperature of the liquid cold plate and pressure drop) has been verified.
Assessment of the derating methods for centrifugal pump performance handling non-Newtonian fluids
Authors: Zanini Nicola , Suman Alessio , Piovan Mattia , Pinelli Michele
Published: December 2023

Oil and Gas applications commonly require the displacement of a huge amount of processing fluids. In most cases, these fluids consist of solid rock particles transported by water, e.g. kaolin or bentonite powder, which show non-Newtonian behavior. For this kind of fluid positive displacement pumps are usually recommended, but where high flow rates have to be guaranteed, centrifugal pumps are installed. Since most of the manufacturers provided the performance curves only with water, choosing the appropriate centrifugal pump to handle mineral slurries may be very challenging. Since the viscosity of this kind of fluids varies with the imposed stress and rheology, pumping this type of fluids can lead to a considerable variation in the pump head, and thus, overall efficiency is difficult to-be-predicted. Several reliable methods to predict the centrifugal pump performance in handling high-viscous Newtonian fluids can be found in literature, e.g. the well-known Hydraulic Institute method. Nevertheless, no general practical correlations are provided for non-Newtonian fluids. Previous experimental investigations on centrifugal pumps reported high-performance instabilities at low flow rates when non-Newtonian fluids are considered. Further investigations are needed to define which parameters in the pump fluid interaction have to be considered in the derating process. In this work, an assessment of the prediction quality of the existing derating methods from the literature is carried out. For this purpose, the data obtained from previous experimental investigations on a small commercial centrifugal pump handling mixtures of water and kaolin are considered.
Discussion on the Application of Integrated Aerogeophysical Method in Urban Site Selection and Construction
Authors: Wang Peijian , Zhang Wei , Li Jiangkun , JunfengLiu  , Deng Zhiqiang , Wang Yuanzhi
Published: December 2023

As the construction of "Belt and Road Initiative" continues to advance, cities and large-scale infrastructure construction will be ushered in along the route, and there is an urgent need to quickly identify the geological situation of the engineering survey needs. Aerial physical prospecting has the characteristics of high efficiency and low cost, which can quickly identify the regional geology in a large area and provide geophysical basis for urban site selection and construction decisions, and has great potential in China’s "Belt and Road Initiative" construction.
Electrical Resistivity Tomography for Urban Underground Space by COMSOL Multiphysics
Authors: Xie Jing , Cui Yi-An , Luo Yijian , Zhang Lijuan , Chen Hang
Published: December 2023

The development and utilization of urban underground space are of great significance to urban sustainable development. Geophysical methods have the characteristics of non-destructive detection, and electrical resistivity tomography has an obvious response to underground resistivity structure and can be used in urban underground space exploration. In this paper, COMSOL Multiphysics is used to realize the finite-element simulation of geoelectric models, and electrical resistivity tomography is used to explore resistivity anomalies of karst and fault models in urban underground environments. The results show that electrical resistivity tomography can identify karst and fault distribution effectively, and COMSOL Multiphysics promises to be a powerful tool for exploring urban underground space.
Research on Multi-dimensional and High-resolution Stereo Detection Technology of Urban Solid Waste Integrated With Open Space
Authors: Liu Wenqiang , Xu Xinxue , Li Chao , Wang Jiaqi , Ma Wei , Wang Junbao
Published: December 2023

The evolution law, waste type, volume and spatial distribution characteristics of a municipal solid waste landfill were studied by using multi-disciplinary comprehensive technologies such as surveying and mapping, geophysics, geological mapping, engineering drilling and three-dimensional modeling. Through the analysis of historical remote sensing and three-dimensional tilt photography data, the evolution law of solid waste is clarified, and the investigation scheme is formulated. With the help of GOCAD three-dimensional modeling software, the high-precision engineering borehole vertical layered positioning and high-resolution horizontal geophysical horizon tracking are organically combined to realize the high-precision and high-resolution intelligent analysis of spatial distribution and volume calculation of solid waste, The three-dimensional exploration system of eco-environmental geological survey is constructed.
A Case Study on Detection of Cavity in Urban Roads Using 3D Ground Penetrating Radar
Authors: Zhou Zhijun , Cui Yongxing
Published: December 2023

In recent years, urban roads collapse accidents often occur, which seriously threatens the safety of people’s lives and property and the order of urban operation, and has a huge social impact. Therefore, it is very necessary to carry out road cavity detection and eliminate the hidden dangers of road operation safety. Three dimensional ground penetrating radar (GPR) technology is a new technology developed in recent years. At present, it has been widely used in road detection. This paper briefly introduces the process of urban roads detection using 3D GPR, and introduces an example of cavity detection. The results show that the effect of 3D GPR in road cavity detection is remarkable, which is worth popularizing.
Near-Surface Radial Anisotropy Tomography of Geothermal Reservoir Using Dense Seismic Nodal Array
Authors: Guan Bo , Xia Jianghai , Liu Ya , Zhang Hao , Zhou Changwei
Published: December 2023

The development and utilization of geothermal energy has become an indispensable part in the process of urbanization in China. Near-surface tomographic imaging based on ambient noise is increasingly widely used in geothermal exploration. To construct the subsurface structure of Shear-wave velocity in Andi town, Zhejiang Province, recordings of ambient noise data of 4.7 days were recorded by a dense seismic array composed of 192 stations with an aperture of about 5 km. Analysis of array beamforming in high-frequency bands indicated the approximately uniformly distributed of noise sources. We applied seismic interferometry to retrieve both Rayleigh and Love waves. We used two-station analysis to obtain dispersion images and the corresponding high-quality dispersion curves were extracted by automated codes. 3-D tomographic results down to a depth of 1.6 km of S-wave velocity structure and radial anisotropy parameters were obtained using direct surface wave radial anisotropy tomography method. The anomalies of S-wave velocity and radial anisotropy parameters were combined to infer the storage of geothermal reservoir in Andi town. Furthermore, the accuracy of our results was verified by the borehole data.
Calculation of Noise Cross-Correlation Functions Between Different Types of Sensors without Removing Instrument Responses
Authors: Liu Ya , Xia Jianghai , Zhang Hao , Guan Bo , Xi Chaoqiang
Published: December 2023

The noise cross-correlation function between two stations provides an efficient way for understanding the subsurface structure. Removing instrument response is a necessary step for the calculation of the noise cross-correlation function (NCF) between different types of sensors, which requires the knowledge of the instrument response. However, the instrument response files may be missing or not provided, restricting us to only the calculation of NCF between the same type of instruments. We propose to calculate the NCF between different sensors deployed at the same site and obtain the phase differences between different instrument responses. The phase differences can then be removed resulting in the unbiased NCF between different sensors deployed at different locations. The effectiveness of our method is verified through a real data example.
Rayleigh Wave Dispersion and Inversion for Shallow Surface with a High-velocity Rigid Pavement
Authors: Zhang Jinyun , Zhang Zhifu , Zhang Yinjie , Lu Xuhan , Jiang Xianhong , Li Peng , Li Kang
Published: December 2023

We investigate the rigid pavement influence on phase velocity dispersion of the Rayleigh wave by using numerical modeling. An overestimation of Rayleigh wave phase velocity is observed more than 10% deviation caused by high-velocity rigid pavement. Based on the generalized reflection and transmission (R/T) coefficient method, the linear eigenvalue problem is solved for vertically heterogeneous media with a rigid pavement structure. The secular function demonstrates the multi-valuedness which is different phase velocity at the same frequency for the single Rayleigh mode. To address mode misidentification problem, we adopt a new misfit function for multimodal dispersion inversion. A Markov chain Monte Carlo (MCMC) sampling algorithm is used to solve dispersion inversion. The synthetic test shows that Rayleigh wave dispersion inversion incorporating a pavement layer can improve estimation accuracy of shear wave velocity.
Detection of Low-Velocity Layer Using Passive Surface-Wave Data and Deep Learning: An Application in The Urban Area of Hangzhou, China
Authors: Chen Xinhua , Xing Huaixue , Pang Jingyin , Zhou Changjiang , Xia Jianghai
Published: December 2023

Passive surface-wave methods using dense seismic arrays have gained growing attention in near-surface high-resolution imaging in urban environments. Deep learning (DL) can release a tremendous workload brought by dense seismic arrays. We presented a case study of shear-wave velocity (Vs) structure imaging in the Hangzhou urban area (eastern China) using DL inversion. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads for investigating the top 80 m of the subsurface. Phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves. We divided the area where the low-velocity layer (LVL) may exist into three layers with a thickness of 5 m. We gave the four layers weak constraints to generate training dataset and adopted a convolutional neural network to directly invert fundamental-mode Rayleigh-wave phase velocity for 1D Vs models. To improve the accuracy, we further applied the sensitivities to weight the loss function in DL inversion. The obtained pseudo-2D Vs profiles correspond to the velocities estimated from logging data and previous survey. The well-trained neural network successfully identified that the LVL is located at 50-60 m deep. And this network was also achieved accurately the inversion of a dense seismic network nearby. The results of this survey demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise using the DL technique, which has great potential for monitoring subsurface changes in urban areas.
Envelope Derivative Operator-based Instantaneous Attributes for Locating Road Cavities
Authors: Hu Xin , Zhang Xuebing , Qiu Zheli , Qin Yuxiang , Song Zhengchun
Published: December 2023

Ground penetrating radar, as an important means of near-surface detection, is being used more and more extensively in road detection. The instantaneous centroid frequency of ground penetrating radar has good directivity for road cavities, and the research of this group further improves the instantaneous centroid frequency for ground-penetrating radar road detection. In this paper, we will model and simulate ground penetrating radar detection to verify the effectiveness of the improved instantaneous pointing frequency.
Multi-parameter Inversion of Tunnels Based on Deep Learning Constraints
Authors: Jiang Peng , Tang Yuting , Liu Benchao
Published: December 2023

When tunnels traverse unfavorable geological formations, they often encounter the risk of sudden water-related incidents, posing a severe threat to the safety of construction workers and property. Consequently, there is an urgent demand for conducting research on the early detection of potential water-related disasters ahead of tunnel excavation. Among the various advanced exploration techniques, the DC resistivity method has proven to be more cost-effective and highly responsive to water-bearing structures, making it a prevalent choice for addressing sudden water hazards in real tunnel projects. This study introduces an innovative electrical approach underpinned by deep learning constraints, fusing resistivity and chargeability to pinpoint the location and size of underground water bodies. More specifically, we’ve designed a learning model rooted in the traditional U-Net convolutional network architecture, featuring a single encoder for feature extraction and a dual decoder for output. When compared to conventional linear inversion techniques and standalone parameter-based deep learning inversion methods, our proposed joint inversion approach exhibits superior performance.
Transdimensional Bayesian Inversion and Uncertainty Estimation of DC Resistivity Data for Undercover Cavern Characterization
Authors: Liu Yajun , Peng Ronghua , Guo Peng , Yu Gang , Liu Lihuang
Published: December 2023

The presence of subsurface karst caverns could pose significant threat to highway construction safety, and the knowledge about the locations and volumes of the caverns is crucial for evaluating potentially hazardous areas. In this work, we present a transdimensional Bayesian approach for characterizing undercover caverns by inverting direct current resistivity data., This approach provides a robust measure of uncertainty associated with the resulting resistivity model. We evaluate the effectiveness of the algorithm on a synthetic 2D resistivity model. The results demonstrate that quantitative uncertainty information on the derived model parameters is vital for reliable data interpretation and facilitates decision making.
Multi-station Magnetotelluric Data Processing Based on Singular Value Decompositionl
Authors: Yin Zihui , Guo Rongwen , Chen Hang
Published: December 2023

Singular value decomposition is an efficient matrix analysis method. This paper intends to use SVD to process magnetotelluric data from multiple stations. The data of multiple magnetotellus observation stations can make the main reactance of magnetotellus obtained by data processing more robust, suppress the interference signal, improve the data quality, and effectively increase the signal strength. The obtained results are more in line with the actual situation, and the decomposition by singular value method can greatly improve the efficiency of electromagnetic signal processing. Better access to underground information, geological resource exploration and deep earth research.
Numerical Simulation of 2D Strong Magnetic Field in Space-Wavenumber Mixed Domain
Authors: Ran Yingqiang , Dai Shikun , Chen Qingrui , Zhang Ying , Ling Jiaxuan
Published: December 2023

Strong magnetic body has self-demagnetization effect, which is not conducive to processing and interpretation of magnetic measurement data. A 2D numerical simulation method in the spatial-wavenumber mixed domain is proposed to calculate magnetic anomalies of 2D strong magnetic objects. In this method, the partial differential equation satisfying the magnetic potential of 2D strong magnetic body is transformed into independent ordinary differential equation between different wave numbers by 1D FFT, which greatly reduces the computation and storage requirements. The compact operator is used to solve the strong magnetic field by iterative method. The algorithm provides a new efficient and high-precision method for the forward modeling of the 2D magnetic anomalies.
A Case Study of Synchrosqueezing Wavelet Transform to Conventional Logging
Authors: Huang Zhaohui , Zang Yongqian , Lai Fuqiang , Jiang Guoqiang , Liu Yuejiao , Liu Yuanqi , Ou Fahui
Published: December 2023

In this paper, the synchronous squeezing wavelet transform (SSWT) is used to process the conventional logging curve, and the spectral characteristics of logging signal are obtained. The results show that the spectral characteristics of SSWT logging in tight sandstone reservoir are more obvious than that in depth domain, and have different characteristics for different reservoir fluid properties, which is helpful to identify the fluid properties of complex reservoirs.
Experimental Study on Influencing Factors of Soil Complex Resistivity
Authors: Han Yalu , Wang Yanlong , Tan Chun , Du Lizhi
Published: December 2023

Complex resistivity is one of the important parameters in electrical prospecting. The application of complex resistivity in oil and gas resource evaluation, engineering investigation and contaminated site evaluation can avoid the influence of low contrast on detection accuracy, and has a good application prospect. In order to improve the study of the influence of soil physical properties on complex resistivity and promote the wider engineering application of complex resistivity exploration. In this paper, the effects of dry density and water content on complex resistivity were studied by laboratory tests, and the following laws were obtained: under the same frequency, the lower the water content of soil sample, the higher the resistivity; The higher the degree of compaction, the lower the resistivity.
Experimental Study on the Performance of Steel Electrodes for Long-term Monitoring
Authors: Feng Shaoting , Yang Dikun
Published: December 2023

Long-term monitoring of electromagnetic (EM) fields requires dense arrays of electrode buried underground for a long time. Steel electrodes are cheap and easy to deploy but are well known to be prone to the noise due to the electrochemical reaction on the metal-fluid interface. In this experiment, we bury an array of steel and non-polarizable electrodes in a realistic monitoring setting, and investigate the performance of steel electrodes with the non-polarizable electrodes as reference. The pilot experiment of 8 days has found significant drift in the data from the steel electrodes, but a detrending process that removes the long-period signals can make the steel and non-polarizable electrode data more consistent at the time scale of a few minutes. The results show that the steel electrodes can have performance comparable with that of the non-polarizable electrodes if signals at relatively short periods are concerned. This study offers inspiration of collecting electrical field data by dense steel electrode arrays for a variety of monitoring applications.
Compression and Reconstruction of Magnetotelluric Data Based on Convolutional Neural Network
Authors: Guo Tianyu , Liu Jianxin , Guo Zhenwei
Published: December 2023

Magnetotelluric method is one of the important geophysical methods, and its signal acquisition requires more stacking times and longer stacking time. With the development of instruments, the acquisition time becomes longer and the amount of data becomes larger, which brings new challenges to data storage and transmission. Aiming at the above problems, a compression and reconstruction technology of magnetotelluric time series based on convolutional neural network is proposed. This paper introduces two convolutional autoencoders based on convolutional neural networks, which can effectively compress data space, improve transmission efficiency, and have high data reconstruction accuracy. Using the measured magnetotelluric time series, two autoencoder models based on convolutional networks are verified in this paper, which proves the feasibility of convolutional autoencoders in magnetotelluric data compression; the results show that model 2 can better reproduce It constructs the magnetotelluric time series, and has high training efficiency and good generalization ability.
Magnetotelluric Time Series Denoising Using Encoder-Decoder Consisted of LSTM Cells
Authors: Wang Sihao , He Lanfang , Wang Xuben , Li Liang
Published: December 2023

Electromagnetic signals in geophysics are frequently disturbed by various interference in field data acquisition. Denoising for passive electromagnetic methods such as magnetotelluric (MT) or audio magnetotelluric (AMT) data is significant to improve data quality and finally imaging to the geoelectrical structure. Conventionally, most denoising methods are employed in frequency domain and few of them are applied in time domain. However, a great number of irregular noise in the electromagnetic time series prove difficulty to be removed. We propose a denoising method, using Encoder-Decoder consisted of Long Short-Term Memory cells (ED-LSTM), to reduce the effect of the step noise and the random-impulsive noise. Supervised learning and transductive learning are used for the denoising of the step noise and the random-impulsive noise, respectively. Our results indicate that the step and random-impulsive noise could be successfully removed from the raw time series. The result indicate that ED-LSTM could potentially to be wildly used in the electromagnetic time series denoising and then improve data quality.