An Innovative System for Testing of Contaminated

0 downloads 0 Views 660KB Size Report
scale. III. DEVELOPED MEASUEREMENT SYSTEM. The apparatus was composed ..... [7] Howard B. Glasgowa,, JoAnn M. Burkholder, Robert E. Reeda , Alan.
An Innovative System for Testing of Contaminated Soft Sediments Francesca Sollecito, Osvaldo Bottiglieri, Federica Cotecchia, Daniela Miccoli, Francesco Todaro, Claudia Vitone Department of Civil, Environmental, Land, Building Engineering and Chemistry Polytechnic University of Bari Bari, Italy [email protected]

Abstract— This paper reports the results of the preliminary mechanical laboratory experiments carried out on the shallowest layer of the polluted submarine clayey sediments of the Mar Piccolo basin (literally “Little Sea”), an inner sea located in Taranto (South of Italy). By the strict cooperation between Geotechnical Engineering and Measurement Science researchers, a test platform has been designed and realised to test samples with fluid-plastic consistency taken within the first meter below the seafloor. The designed measurement system and the suggested procedure of acquisition and data processing allow for a reliable marine behaviour assessment and they ensure both the human safety and the sample quality. Keywords—Geotechnical characterisation, polluted sediments, laboratory tests, automatic test system, linear displacement transducers.

I.

INTRODUCTION

The growing attention devoted to monitor and assess the quality of both sea water and soil led to the development of new techniques and innovative network sensors for the marine pollution assessment and the environmental remediation [1][8]. The present work has dealt with some experimental complexities arising from the geotechnical investigation of the marine sediments from the Mar Piccolo basin (Taranto city, south of Italy – Fig. 1), due to the very soft consistency of the sediments collected in the top layer (0-1m below the seafloor) and the high levels of contaminants. The Mar Piccolo basin is divided into the so-called First and Second Bay (Fig. 1) and is characterised by a total surface of about 20 km2 and 13 m of maximum water depth. Because of the heavy industrialisation experienced by the Taranto city during the last 50 years, the complex ecosystem of the Mar Piccolo basin started exhibiting unconfutable signs of environmental pollution enhanced by several uncontrolled discharged sewages, the activities of the Marine Arsenal of the main naval base of the Italian Navy and the fishing-boat fleet. Several researchers [9]-[15] have shown that the submarine sediments in the basin contain high concentrations of heavy metals (e.g. mercury Hg, lead Pb, cadmium Cd, copper Cu and zinc Zn) and organic pollutants (polychlorinated biphenyls PCBs, polycyclic aromatic hydrocarbons PAHs and dioxins) that can even exceed the law limits [16]. Probably, due to the inflow of fresh water by submarine springs (e.g. Galeso and Citrello in Fig.1) and tributary rivers, the peculiar morphology and the climatic conditions of the area, the Mar Piccolo represents an unusual ecosystem from the naturalistic point of view and the most important area of mussel farming in Italy. In 2016-2017 an ample investigation campaign was funded by

Francesco Adamo, Gregorio Andria, Attilio Di Nisio, Anna Maria Lucia Lanzolla, Maurizio Spadavecchia Department of Electrical and Computer Science Engineering Polytechnic University of Bari Bari, Italy [email protected]

the Special Commissioner for urgent measures of reclamation, environmental improvements and redevelopment of Taranto (CS_2017 campaign, hereafter), aimed to the interdisciplinary investigation of the environmental properties of the sediments in the First Bay [17]. The project involved experts from several research fields (i.e. biology, chemistry and geochemistry, geology, hydrology and hydrogeology, hydraulic, geo-technologist, geotechnical and electrical engineering) and public research institutions (i.e. Polytechnic University of Bari, University of Bari “Aldo Moro”, National Research Council, CNR), which cooperated to characterise the geo-chemo-mechanical state of such a severely polluted basin. In this context, the geotechnical characterisation of the polluted sediments required the development of innovative solutions to consider the complexities deriving by the highly variable consistency of the sediments, the presence of shells, organic matter and pollutants, and the salinity of the pore fluid. It follows that some novelties have been introduced in the phase of soil testing, to preserve both the human safety and the sample quality. II.

TEST PROCEDURES

The mechanical testing on representative soil specimens are usually performed in a geotechnical laboratory to investigate the main soil mechanical properties, such as compressibility and shear strength. However, these tests on soft contaminated sediments are challenging since the finegrained soils are usually characterised by very low consistency and high fluid content, as in the case of the shallow layer of sediments (1-1.5m bsf) collected in the Mar Piccolo basin [18].

Fig. 1. Mar Piccolo basin in Taranto (Southern Italy) and sampling sites of the investigation campaign supported by the Special Commissioner (CS_2017, green dots). The figure also shows some of the industrial activities around the basin, the mussel farming areas (white contours) and the main submarine springs.

One of the main concerns is the preparation of undisturbed specimens at the in-situ state for triaxial tests [19], which is the most widely used test to determine the soil shear strength parameters and the isotropic compressibility. Indeed, the triaxial text requires the preparation of an undisturbed cylindrical specimen (usually 38 mm diameter – 76 mm high), which is enclosed in a latex membrane and placed on a base platen, without rigid lateral confinement. This aspect makes particularly hard the preparation of the undisturbed triaxial specimens that are representative of the site conditions in case of sediments of fluid consistency.

engineering laboratory tests. The management software was developed thanks to the strict cooperation between Geotechnical Engineering and Measurement Science researchers. One of the most interesting features introduced by the system is the remote test monitoring through networking techniques to minimize the operators’ exposition to contaminants during the testing time. In particular, the modulus used to manage the consolidometer test was created for the standard geotechnical one-dimensional tests, i.e. the Oedometer Tests [22].

In addition, when dealing with contaminated sediments, the characterisation of the pore fluid extracted during the consolidation process could be helpful for the assessment of the mobility of the contaminant inside the porous media under the effect of a vertical load. Although contaminants may be removed from sediments by using various remediation methods, a cover or cap placed in situ at the top of the contaminated deposit is one of the possible types of remediation strategies. Hence, there is always a concern that the contaminants present in the sediments may mobilize and migrate into the overlying water as an effect of direct load [20] due to the induced advection, but also to mechanical dispersion and diffusion phenomena. Therefore, a crucial issue is the determination of both the consolidation features of the sediments and the properties of the pore fluid expelled during the consolidation process under the applied load.

Software description The control software of the new measurement system is developed in LabVIEW® that is a useful tool able to the easy interface with several data acquisition (DAQ) systems and to simplify both the software development and the hardware reconfiguration in case of necessity. It manages all tests and the sensors calibration procedures, showing as much information as possible and keeping track of all the history of the measurands. Then, it is widely used in many application fields such as data acquisition and control systems condition monitoring for power generation and devices characterisation [23]-[27].

This work presents the setup of a consolidometer that was designed and realised to consolidate the samples with fluid consistency taken within the first meter below the seafloor in the Mar Piccolo basin. Once the sample has been extracted from the consolidometer its consistency is suitable for preparing triaxial specimens. At the same time, the apparatus allows the extraction and the collection of the pore fluid which comes out during the one-dimensional compression of the sample. Lastly, the chemical characterisation of the fluid collected at different load steps enable the researcher to investigate if the contaminants are free to move in the porous media when subjected to a vertical load. This apparatus allows both to simulate the processes naturally occurring in the sediments, when pore fluid flows out as the soil is subjected to load, and to monitor the whole process at the laboratory scale. III.

DEVELOPED MEASUEREMENT SYSTEM

The apparatus was composed by a stainless-steel pedestal equipped with drainage lines connected to thin tubes for the collection of pore fluid, which ended up in a high-density polyethylene bottle. Instead of a standard metallic tube, a transparent polycarbonate tube 5 mm thick was used, as the polycarbonate is non-reactive with most of the contaminants and it has higher stiffness than other plastic materials, so as to prevent the lateral deformations of the specimen during the one-dimensional consolidation process. A Linear Displacement Transducers (LTD) based on strain-gauge bridge was installed at the top of the specimen to record its settlements during throughout the consolidation phase. The displacements were registered by one of the software modules of an original automated measurement system, named “GeoLab” [21], developed to both acquire and process data coming from different tests with the aim to increase speed and accuracy, to reduce the risk of human mistakes and, more generally, to improve the productivity during geotechnical

Many software modules were created, one for each possible test; also, a semi-automated calibration procedure for each kind of test and sensor set was created. Each module has a user-friendly interface (Fig. 2) and was purposely developed to acquire signals from the transducers mounted on each testing apparatus and to monitor the changes of each measurand (i.e. displacement, load and pressure) when the specimen is loaded. Moreover, some parameters such as temperature, sensor supply voltage and offset of the acquisition channel can be acquired, using suitable accessories, to study their influences on measurements. The calibration software acquires continuously voltage signal from the channel of the DAQ where the transducer under calibration is connected. A graphical display shows the actual sampled buffer whereas two numerical displays show the mean and the standard deviation of the signal. When these values are stable, the value of the measurands (read, for example, using a micrometre in the case of displacement transducer) is manually input by the user thus the values of measurand and corresponding voltage are stored and directly displayed. This procedure is generally repeated both for increasing and decreasing values, eventually many times to assess hysteresis and repeatability errors. At the end of this process, slope, intercept and correlation coefficient of the linear regression are automatically estimated. The software can also assess nonlinear models such as polynomial and exponential ones, or use different fitting methods, showing the fitting equation. The data acquisition module was subdivided into two subVIs, configuring a producer/consumer scheme from the data flow point of view: the first subVI (the data server) is devoted to communicating with the DAQ board thorough the proper driver and to acquiring signals buffering them in a FIFO queue. Since geotechnical experiments are generally long-lasting tests due to the very low soil permeability (i.e. the soil permeability, k, varies between about 10-5 and 10-14 m/s, passing from sandy to clayey soils [28]), a fundamental sample rate of 0.1 s was considered sufficient to analyse fast phenomena; thus, the sampling rate of each channel may be configured as a multiple of this fundamental sampling time.

Indeed, each measurement (each element of the queue) is the mean over 1000 samples acquired at 10 kHz sampling frequency to filter possible outliers and to improve the measurement accuracy. Moreover, for DAQ boards supporting this feature, an autocalibration procedure is automatically made every 30 minutes to minimize errors due to thermal drift of the DAQ board itself. The second subVI (the data client) gathers the data values from the first subVI and plots them on the graph; it also grants to the operator the ability to configure each channel as needed by the particular experiment; each channel may be set in term of channel type (Referenced Single Ended/Not Referenced Singe Ended/Differential), scale factor, sample rate, etc. All test parameters are set through a cluster of user interface controls containing basic information (calibration constants, sampling rate, offset and mechanical zero, applied load, etc.). A graph reporting the transduced variables for the OT measurement system is shown in Fig. 2. The OT interface in the figure shows the time variation of the vertical displacement, that is the evolution of the consolidation process of the specimen during a single loading step. All configuration values are exchanged between front panels and block diagrams using a set of global variables and references to controls or indicators. This is the case, for example, to route data from each transducer to the proper graph or log-file. This solution makes it possible to have a hardware-independent software with a high degree of flexibility to front possible changes either in channel numbers or in the type of trials. Raw and scaled data are continuously stored in a Comma Separated Values (CSV) log file corresponding to a single test apparatus with all calibration coefficients and timestamps, so that researchers can also post-process data for further analysis. Each log file may receive data from one (in the case of OT) or more DAQ channels depending on the test. Near real-time plots are available during the data acquisition.

An optimal solution is the direct connection to the user interface of the management software by activating a dedicated web server using features natively implemented in LabVIEW thus avoiding the use of third-party software modules such internet browser, Remote Desktop or Virtual Network Computing. The main advantage is the great responsivity of the user interface in terms of both response to remote commands and of low latency in displaying of data graphs. Hardware description From the hardware point of view, this research has required an intense work for the designing and prototyping of the signal acquisition control boxes. The most di cult aspects of the work were the large number of sensing points and the relatively long distances between them and the control PC (in some case >10 m); these aspects had imposed the design of: wall-mounted boxes containing the DAQ devices and a signal routing PCB (printed circuit board) with per-channel configurable low- pass filters and precision high output current voltage references to excite the transducers. Fig. 3 shows two pictures of the data-acquisition cabinets designed for this project. Each cabinet contains a 13 V power supply, and three voltage reference modules, for exciting different transducers; 16 connection ports are available, where the voltage supplied to each port can be selected among those available (namely 13, 10 and 5 V) using a three-position slider switch placed alongside each connection port. The voltage reference modules are modular since they have snap-in connectors for a quick and easy replacement in case of failure or to modify the output voltage substituting the voltage divider resistors.

One of the most interesting features introduced with the system here presented is the remote monitoring through networking techniques. The networking was required also to allow the test control by different faraway laboratories, making it possible either the cooperation between the research groups or the inter-laboratory data validation. Then, di erent solutions have been developed ranging from the simple monitoring of the tests by means of a common web-browser to the full control of the testing interface using web-based or built-in solutions. Fig. 3. External and Internal view of one data acquisition cabinet based on a National Instruments’ USB DAQ device.

IV.

Fig. 2. Screenshot of the OT operator’s interface.

TEST RESULTS

A laboratory characterisation of these modules was performed using an automated test setup made by a Hockerl & Hackl ZSHW20D programmable load, a Keysight E3631A triple output power supply used as a primary power source and a Keysight E34401A benchtop 6 1/2 digits digital multimeter used to accurately measure the module output voltage under the different load conditions, with output current spanning the range 0–300 mA.

All these instruments were connected to a PC with an IEEE488 bus and the test procedure was controlled by a MATLAB script. Fig. 4 shows the output voltage normalized by the no-load value. To improve the measurement accuracy, the voltage of each characterisation point was obtained as a mean of 100 measures. As it can be seen, the relative variation in output voltage is less than 0.1% of the no-load value over the entire span of output current. This variation is surely acceptable for the considered application, also given that almost all measures are done in a ratiometric way, that is the excitation voltage of sensors is measured and used as a reference for all measures.

V.

CONCLUSION

The experimental programme carried out on the polluted submarine sediments from Taranto allowed to both study and define some new procedures for a suitable handling and characterisation of samples of soft consistency, rich in pollutants, organic matter and salts. In this context, a consolidometer apparatus has been developed and tested to both consolidate the shallow samples and to enable the preparation of the specimens for triaxial tests. In addition, the consolidometer could be used to collect simultaneously the likely contaminated pore fluid extracted from the specimen during the consolidation phase. The software developed thanks to the strict cooperation between Geotechnical Engineering and Measurement Science researchers has been used to record the settlements of the specimen during the consolidation process and infer its compressibility during 1D loading. Possible advances in the apparatus could be the introduction of both local displacement transducers and probes for measuring the pore fluid contamination. ACKNOWLEDGEMENTS

Fig. 4. Normalized output voltage of one reference generator module as a function of the load current.

The activities described in this publication were funded by the Special Commissioner for urgent measures of reclamation, environmental improvements and redevelopment of Taranto (South of Italy), Dr Vera Corbelli [17]. REFERENCES

This measurement method also protects from the small reference voltage drift due to components aging; thermal drifts are almost absent because temperature and humidity of the experiment are both controlled by a dedicated HVAC (Heating, Ventilation and Air Conditioning) system which guarantees the temperature stability in a range± 0.5 °C around the nominal value of the test rooms. Fig. 5 shows the one-dimensional compression behaviour of one shallow specimen (0-1m bsf) in the void ratio, e vertical effective stress, σ’v, semi-logarithmic plot obtained after eight loading steps in the consolidometer apparatus. At σ’v equal to 100 kPa, the specimen has been extracted and mounted into a triaxial test apparatus for its shear strength characterisation. In addition, the pore fluid extracted during the consolidation phase has been collected and analysed in a chemical laboratory.

[1]

[2]

[3]

[4]

[5]

4.5 4.0

[6]

3.5

e [-]

3.0 2.5 2.0 1.5

[7]

1.0 0.5 0.0 1

10

σ'v [kPa]

100

1000

Fig. 5. Compression behaviour of one shallow specimen (0-1m bsf) obtained by the consolidometer test.

[8]

[9]

N.A Cloete, R. Malekian, L. Nair, “Design of Smart Sensors for RealTime Water Quality Monitoring” , IEEE Acess, vol. 4, 2016, pp. 39753990. G. Andria, G. Cavone, V. Di Lecce, A. M. L. Lanzolla, “Model Characterization of Measurement Environmental Pollutants via data Correlation of Sensor Output”, IEEE Trans, on Instrumentation and Measurement, vol. 54, pp. 1061-1066, 2005. F. Lamonaca, D.L. Carni, M. Riccio, D. Grimaldi, G. Andria “Preserving Synchronization Accuracy from the Plug-in of NonSynchronized Nodes in a Wireless Sensor Network”, IEEE Transactions on Instrumentation and Measurement, vol. 66, no 5, pp. 1058-1066, May 2017. M. C. Falconi, G. Palma, F. Starecki, V. Nazabal, J. Troles, S. Taccheo, M. Ferrari, F. Prudenzano, “Design of an Efficient Pumping Scheme for Mid-IR Dy3+:Ga5Ge20Sb10S65 PCF Fiber Laser” , IEEE Photonics Technology Letters, vol. 28, no. 18, pp. 1984-1987, September 2016. L. Lombardo, J. Zhang, S.G. Leonardi, D. Aloisio, G. Neri, D. Li, N. Donato, "A portable system for the monitoring of dissolved oxygen in aquatic environment", Lecture Notes in Electrical Engineering", vol. 409, pp. 67-73, 2017. L. Cilenti, R. Dario, G. Dentamaro, V. Di Lecce, C. Guaragnella, A. Cardellicchio, G.Mancinelli, D. Petruzzelli, A. Quarto, D. Soldo, D.e, A. Specchiulli, I. Zacharias, “Sea water distributed monitoring system: A proposal for architecture and data format”, 2018 IEEE International Conference on Environmental Engineering, EE 2018 – Proceedings, 13 June 2018, pp. 1-7 Howard B. Glasgowa,, JoAnn M. Burkholder, Robert E. Reeda , Alan J. Lewitusb, Joseph E. Kleinmana, “Real-time remote monitoring of water quality: a review of current applications, and advancements in sensor, telemetry, and computing technologies”, Journal of Experimental Marine Biology and Ecology vol. 300, pp. 409 – 448, 2004 M. C. Falconi, G. Palma, F. Starecki, V. Nazabal, J. Troles, J.-L. Adam, S. Taccheo, M. Ferrari, F. Prudenzano, “Dysprosium-Doped Chalcogenide Master Oscillator Power Amplifier (MOPA) for Mid-IR Emission,” Journal of Lightwave Technology, vol. 35, no. 2, pp. 265273, January. 2017 Cardellicchio N., Buccolieri A., Giandomenico S., Lopez L., Pizzulli F., Spada L. 2007. Organic pollutants (PAHs. PCBs) in sediments from

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

the Mar Piccolo in Taranto (Ionian Sea. Southern Italy). Marine Pollution Bullettin, 55, pp. 451–458. Di Leo A., Annicchiarico C., Cardellicchio N., Spada L. and Giandomenico S. 2013. Trace metal distributions in Posidonia oceanica and sedimentsfrom Taranto Gulf (Ionian Sea, Southern Italy). Mediter Marine Science 14(1), 204–213 ICRAM-APAT. 2007. Manuale per la movimentazione di sedimenti marini.Technical report. http://www.isprambiente.gov.it/contentfiles/ 00006700/6770-manuale-apat-icram-2007. ISPRA. 2010. Elaborazione e valutazione dei risultati della caratterizzazione ai fini della individuazione degli opportuni interventi di messa in sicurezza e bonifica del Sito di Interesse Nazionale di Taranto - Mar Grande II Lotto e Mar Piccolo. Report 2010. A. Federico, C. Vitone, A. Murianni, “On the mechanical behaviour of dredged submarine clayey sediments stabilized with lime or cement”, Canadian Geotechnical Journal, vol. 52, no. 12, pp. 2030-2040, 2015. F. Attivissimo, C. Guarnieri Calò Carducci, A.M.L. Lanzolla, A Massaro, M.R. Vadrucci, “A portable optical sensor for sea quality monitoring”, IEEE Sensors Journal, vol. 15, no. 1, pp. 146-153, January 2015 . Petronio BM, Cardellicchio N, Calace N, Pietroletti M, Pietrantonio M, Caliandro L. 2012. Spatial and temporal heavy metal concentration (Cu, Pb, Zn, Hg, Fe, Mn, Hg) in sediments of the Mar Piccolo in Taranto. Water Air Soil Pollut. doi:10.1007/s11270-011-0908-4. Italian Law n. 152. 2006. Norme in materia ambientale. Gazzetta Ufficiale della Repubblica Italiana n. 88 del 14 aprile 2006 Supplemento Ordinario n. 96. Accordo di collaborazione ai sensi dell’art. 15 della L. 241/1990, stipulato in data 2/12/2014 tra il Commissario Straordinario per gli interventi urgenti di bonifica, ambientalizzazione e riqualificazione di Taranto e il Politecnico di Bari. C. Vitone, A. Federico, A. Puzrin, M. Plotze, E. Carrassi, F. Todaro, “On the geotechnical characterisation of the polluted submarine sediments from Taranto”, Environmental Science and Pollution Research Journal, vol. 23, no. 13, pp. 12535-12553, 2016.

[19] ASTM D4767-11, Standard Test Method for Consolidated Undrained Triaxial Compression Test for Cohesive Soils, ASTM International, West Conshohocken, PA, 2011, www.astm.org [20] Erten M. B., Gilbert R.B., El Mohtar C.S., Reible D.D. 2011. Development of a Laboratory Procedure to Evaluate the Consolidation Potential of Soft Contaminated Sediments. Geotechnical Testing Journal, Vol. 34, No. 5. [21] F. Adamo, G. Andria, O. Bottiglieri, F. Cotecchia, A. Di Nisio, D. Miccoli, F. Sollecito, M. SpadavecchiaF. Todaro, A. Trotta, C. Vitone, “GeoLab, a measurement system for the geotechnical characterization of polluted submarine sediments”, Measurement,vol. 127, October 2018, pp. 335-347. [22] ASTM D2435 / D2435M-11, Standard Test Methods for OneDimensional Consolidation Properties of Soils Using Incremental Loading, ASTM International, West Conshohocken, PA, 2011, www.astm.org. [23] F. Adamo, F. Attivissimo, A. Di Nisio, M. Savino, e M. Spadavecchia, “A Spectral Estimation Method for Nonstationary Signals Analysis with Application to Power Systems”, Measurement: Journal of the International Measurement Confederation, vol. 73, pagg. 247–261, 2015. [24] C. Guaranieri Calò Carducci, M. Marracci, F. Attivissimo R. Giannetti, B. Tellini, “An Improved DAQ-Based Method for Ferrite Characterization”, IEEE Transactions on Instrumentation and Measurement, vol. 66, no. 9, September 2017, pp. 2413 – 2421. [25] F. Adamo, G. Cavone, A. Di Nisio, A..M.L Lanzolla, M. Spadavecchia, “A proposal for an open source energy meter”, 2013 IEEE International Instrumentation and Measurement Technology Conference, May 2013, Minneapolis, pp. 488-492 [26] E. Koutroulis, K. Kalaitzakis “Development of an integrated dataacquisition system for renewable energy sources systems monitoring”, Renewable Energy, vol. 28, no.1, January 2003, pp. 139-152. [27] F. Attivissimo, C. Guarnieri Calò Carducci, A. M. L. Lanzolla, e M. Spadavecchia, “An Extensive Unified Thermo-Electric Module Characterization Method”, Sensors, vol. 16, n. 12, pag. 2114, dic. 2016. [28] R. Lancellotta, “Geotecnica”, Zanichelli, Bologna, 1993.

Suggest Documents