20 research outputs found
Studio delle trasformazioni dell’austenite negli acciai multifase innovativi
La famiglia degli acciai multifase include gli acciai Dual-Phase (DP), TRIP, a fasi complesse (CP) e martensitici (MS). Le proprietà di questi materiali sono date principalmente dalla combinazione delle componenti microstrutturali con diversi gradi di durezza. Le strutture degli acciai multifase sono ottenute attraverso una specifica combinazione dei parametri di laminazione e della strategia di raffreddamento. Le trasformazioni dell’ austenite negli acciai multifase sono uniche. La combinazione di alta resistenza e buona formabilità è data dal particolare ciclo termico che prevede il raffreddamento da zona intercritica (da una temperatura compresa tra A1 e A3): l’ austenite ha quindi un tenore di carbonio diverso dall’ acciaio di base che è funzione della temperatura intercritica, inoltre la ferrite non viene generata da una fase di nucleazione e accrescimento, ma solo dalla fase di accrescimento. La predizione delle curve CCT per questi acciai riveste particolare importanza in quanto prevedendo la microstruttura finale si riesce a predirne le proprietà meccaniche
Hazards and safety issues associated to the residual solid content in crude edible oil processing
The present work focuses on the hazards connected with edible oil refining during process and maintenance operations. A specific experimental protocol was set up in order to verify the possibility of having fire hazards connected with the unwanted residual solids which might accumulate on the bottom of storage tanks, due to sedimentation, or in process equipment, due to progressive fouling. The analysis of residual solid samples taken from an actual edible oil refinery allowed evaluating the possible formation of flammable mixtures or products during maintenance operations. Specific hazard indexes were defined in order to analyse two case studies which provided indications for the safety enhancement of process and maintenance operations
ENPP1 Affects Insulin Action and Secretion: Evidences from In Vitro Studies
The aim of this study was to deeper investigate the mechanisms through which
ENPP1, a negative modulator of insulin receptor (IR) activation, plays a role on
insulin signaling, insulin secretion and eventually glucose metabolism. ENPP1
cDNA (carrying either K121 or Q121 variant) was transfected in HepG2 liver-, L6
skeletal muscle- and INS1E beta-cells. Insulin-induced IR-autophosphorylation
(HepG2, L6, INS1E), Akt-Ser473,
ERK1/2-Thr202/Tyr204 and GSK3-beta Ser9
phosphorylation (HepG2, L6), PEPCK mRNA levels (HepG2) and
2-deoxy-D-glucose uptake (L6) was studied. GLUT 4 mRNA
(L6), insulin secretion and caspase-3 activation (INS1E) were also investigated.
Insulin-induced IR-autophosphorylation was decreased in HepG2-K, L6-K, INS1E-K
(20%, 52% and 11% reduction vs. untransfected cells) and
twice as much in HepG2-Q, L6-Q, INS1E-Q (44%, 92% and 30%).
Similar data were obtained with Akt-Ser473,
ERK1/2-Thr202/Tyr204 and GSK3-beta Ser9 in
HepG2 and L6. Insulin-induced reduction of PEPCK mRNA was progressively lower in
untransfected, HepG2-K and HepG2-Q cells (65%, 54%, 23%).
Insulin-induced glucose uptake in untransfected L6 (60% increase over
basal), was totally abolished in L6-K and L6-Q cells. GLUT 4 mRNA was slightly
reduced in L6-K and twice as much in L6-Q (13% and 25% reduction
vs. untransfected cells). Glucose-induced insulin secretion was 60%
reduced in INS1E-K and almost abolished in INS1E-Q. Serum deficiency activated
caspase-3 by two, three and four folds in untransfected INS1E, INS1E-K and
INS1E-Q. Glyburide-induced insulin secretion was reduced by 50% in
isolated human islets from homozygous QQ donors as compared to those from KK and
KQ individuals. Our data clearly indicate that ENPP1, especially when the Q121
variant is operating, affects insulin signaling and glucose metabolism in
skeletal muscle- and liver-cells and both function and survival of insulin
secreting beta-cells, thus representing a strong pathogenic factor predisposing
to insulin resistance, defective insulin secretion and glucose metabolism
abnormalities
A neural networks-based model relating properties of the as cast-semi and rolling parameters with rolled product properties for plate rolled pipeline steels
Segregation is an important phenomenon which heavily affects the final mechanical properties of steel products. The presence of several complex physical phenomena resulting in final segregation pattern in as-cast products makes the quantitative prediction of macro-segregation for industrially relevant casting processes extremely difficult. In the present work, a reliable prediction of important rolled product quality (in terms of mechanical and Charpy impact properties) which are linked to segregation is achieved for plate rolled pipeline steels by exploiting data related to the as-cast structure and caster operational data (including casting machine condition) through the application of neural networks. In particular, a hierarchical approach is proposed for the prediction of the Charpy Impact Value, in order to reflect the physical link between this quantity and the Ultimate Tensile Strength. The neural predictor has been developed by exploiting real industrial data and its performance can improve through time by enlarging the database that is used for its training
A Finite Element Method for the Prediction of Thermal, Metallurgical, and Mechanical Behaviour of Rebars in the TempCore Process
Diagnosis of the instability of the cooling behaviour of flat steel products through parametric characterisation, neural networks and statistics
This paper presents a mathematical model developed by means of an analytical function whose shape depends on the values of a few parameters for the run-out table cooling which is used in hot strip mills. The system relies on a first-order differential equation for describing the temperature loss along the run-out table. Neural networks have been applied in order to find correlations between the model parameters and the steel and process variables. Then, traditional statistical techniques have been applied in order to evaluate the stability of the cooling behaviour. Numerical results obtained on an industrial database are presented and discussed
Strain Hardening Behaviour Prediction Model For Automotive High Strength Multiphase Steels
Prediction of continuous cooling transformation diagrams for dual-phase steels from the intercritical region
The purpose of the present work is the implementation and validation of a model able to predict the microstructure changes and the mechanical properties in the modern high-strength dualphase steels after the continuous annealing process line (CAPL) and galvanizing (Galv) process. Experimental continuous cooling transformation (CCT) diagrams for 13 differently alloying
dual-phase steels were measured by dilatometry from the intercritical range and were used to tune the parameters of the microstructural prediction module of the model. Mechanical properties and microstructural features were measured for more than 400 dual-phase steels simulating the CAPL and Galv industrial process, and the results were used to construct the
mechanical model that predicts mechanical properties from microstructural features, chemistry, and process parameters. The model was validated and proved its efficiency in reproducing the
transformation kinetic and mechanical properties of dual-phase steels produced by typical industrial process. Although it is limited to the dual-phase grades and chemical compositions explored, this model will constitute a useful tool for the steel industry